source: doc/genius.bib

@article {Genius,
        title = {Genius: An Integrated Environment for Supporting the Design of Generic Automated Negotiators},
        journal = {Computational Intelligence},
        year = {2012},
        publisher = {Blackwell Publishing Inc},
        abstract = {The design of automated negotiators has been the focus of abundant research in recent years. However, due to difficulties involved in creating generalized agents that can negotiate in several domains and against human counterparts, many automated negotiators are domain specific and their behavior cannot be generalized for other domains. Some of these difficulties arise from the differences inherent within the domains, the need to understand and learn negotiators{\textquoteright} diverse preferences concerning issues of the domain, and the different strategies negotiators can undertake. In this paper we present a system that enables alleviation of the difficulties in the design process of general automated negotiators termed Genius, a General Environment for Negotiation with Intelligent multi-purpose Usage Simulation. With the constant introduction of new domains, e-commerce and other applications, which require automated negotiations, generic automated negotiators encompass many benefits and advantages over agents that are designed for a specific domain. Based on experiments conducted with automated agents designed by human subjects using Genius we provide both quantitative and qualitative results to illustrate its efficacy. Finally, we also analyze a recent automated bilateral negotiators competition that was based on Genius. Our results show the advantages and underlying benefits of using Genius and how it can facilitate the design of general automated negotiators.},
        issn = {1467-8640},
        doi = {10.1111/j.1467-8640.2012.00463.x},
        url = {http://dx.doi.org/10.1111/j.1467-8640.2012.00463.x},
        attachments = {http://mmi.tudelft.nl/sites/default/files/genius_0.pdf},
        author = {Raz Lin and Sarit Kraus and Tim Baarslag and Dmytro Tykhonov and Koen V. Hindriks and Catholijn M. Jonker}
}

@article {MultilateralOffersProtocols,
        title = {Alternating Offers Protocols for Multilateral Negotiation},
        journal = {Modern Approaches to Agent-based Complex Automated Negotiation},
        year = {2014},
        publisher = {Springer},
        abstract = {This paper presents a general framework for multilateral turn-taking protocols and two fully specified protocols namely Stacked Alternating Offers Protocol (SAOP) and Alternating Multiple Offers Protocol (AMOP). In SAOP, agents can make a bid, accept the most recent bid or walk way (i.e., end the negotiation without an agreement) when it is their turn. AMOP has two different phases: bidding and voting. The agents make their bid in the bidding phase and vote the underlying bids in the voting phase. Unlike SAOP, AMOP does not support walking away option. In both protocols, negotiation ends when the negotiating agents reach a joint agreement or some deadline criterion applies. The protocols have been evaluated empirically, showing that SAOP outper- forms AMOP with the same type of conceder agents in a time-based deadline setting. SAOP was used in the ANAC 2015 competition for automated negotiating agents.},
        issn = {978-3-319-30307-9},
        author = {Reyhan Aydogan and David Festen and Koen V. Hindriks and Catholijn M. Jonker}
}

@incollection{MultiMediatedNegoProtocolsWithFeedback,
  author       = {Reyhan Aydogan and Koen V. Hindriks and Catholijn M. Jonker}, 
  title        = {Multilateral Mediated Negotiation Protocols with Feedback},
  editor      = "I. Marsa-Maestre and M. A. Lopez-Carmona and T.  Ito and M. Zhang and  Q. Bai and K. Fujita",
  booktitle   = "Novel Insights in Agent based Complex Automated Negotiation, Chapter: Multilateral Mediated Negotiation Protocols with Feedback",
  publisher   = "Springer",
  year        = 2014,
  pages        = {43-59},
  chapter     = 3,
}

% Encoding: UTF-8

@InProceedings{Tsi18,
 title                = {Automated Negotiations under User Preference Uncertainty: A Linear Programming Approach},
 author               = {Tsimpoukis, Dimitrios and Baarslag, Tim and Kaisers, Michael and Paterakis, Nikolaos},
 booktitle            = {Proceedings of Agreement Technologies},
 year                 = 2018,
 month                = Jan,
 url                              = {https://ir.cwi.nl/pub/28326/2018_AT_Tsimpoukis.pdf}
}

@inproceedings{Diplomacy20172018,
  title={The Challenge of Negotiation in the Game of Diplomacy},  
  author={Dave de Jonge and Tim Baarslag and Reyhan Aydo{\u{g}}an and Catholijn Jonker and Katsuhide Fujita and Takayuki Ito},
  booktitle={The 6th International Conference on Agreement Technologies (AT2018)},
  year={2018},
  url={https://docs.wixstatic.com/ugd/38cae9_0c5b5c80a34346eab844c3bd70555af5.pdf}
}

@article{Zaf19,
title = "Modelling and analysis of temporal preference drifts using a component-based factorised latent approach",
journal = "Expert Systems with Applications",
volume = "116",
pages = "186 - 208",
year = "2019",
issn = "0957-4174",
doi = "https://doi.org/10.1016/j.eswa.2018.09.010",
url = "http://www.sciencedirect.com/science/article/pii/S0957417418305815",
author = "Farhad Zafari and Irene Moser and Tim Baarslag",
keywords = "Latent factor models, Bias, Feature preferences, Feature value preferences, Temporal dynamics, Preference drift",
abstract = "In recommender systems, human preferences are identified by a number of individual components with complicated interactions and properties. Recently, the dynamicity of preferences has been the focus of several studies. The changes in user preferences can originate from substantial reasons, like personality shift, or transient and circumstantial ones, like seasonal changes in item popularities. Disregarding these temporal drifts in modelling user preferences can result in unhelpful recommendations. Moreover, different temporal patterns can be associated with various preference domains, and preference components and their combinations. These components comprise preferences over features, preferences over feature values, conditional dependencies between features, socially-influenced preferences, and bias. For example, in the movies domain, the user can change his rating behaviour (bias shift), her preference for genre over language (feature preference shift), or start favouring drama over comedy (feature value preference shift). In this paper, we first propose a novel latent factor model to capture the domain-dependent component-specific temporal patterns in preferences. The component-based approach followed in modelling the aspects of preferences and their temporal effects enables us to arbitrarily switch components on and off. We evaluate the proposed method on three popular recommendation datasets and show that it significantly outperforms the most accurate state-of-the-art static models. The experiments also demonstrate the greater robustness and stability of the proposed dynamic model in comparison with the most successful models to date. We also analyse the temporal behaviour of different preference components and their combinations and show that the dynamic behaviour of preference components is highly dependent on the preference dataset and domain. Therefore, the results also highlight the importance of modelling temporal effects but also underline the advantages of a component-based architecture that is better suited to capture domain-specific balances in the contributions of the aspects.",
pdf = "pub/Modelling_and_Analysis_of_Temporal_Preference_Drifts_Using_a_Component-based_Factorised_Latent_Approach.pdf"
}

@inproceedings{ANAC2017,
  title={{ANAC} 2017: Repeated Multilateral Negotiation League},
  author={Reyhan Aydo{\u{g}}an and Katsuhide Fujita and Tim Baarlag and Catholijn M. Jonker and Takayuki Ito},
  booktitle={The 11th International Workshop on Automated Negotiation, ACAN 2018},
  year={2018},
}

@inproceedings{IAGO2017,
 author = {Mell, Johnathan and Gratch, Jonathan and Baarslag, Tim and Aydo\u{g}an, Reyhan and Jonker, Catholijn M.},
 title = {Results of the First Annual Human-Agent League of the Automated Negotiating Agents Competition},
 booktitle = {Proceedings of the 18th International Conference on Intelligent Virtual Agents},
 series = {IVA '18},
 year = {2018},
 isbn = {978-1-4503-6013-5},
 location = {Sydney, NSW, Australia},
 pages = {23--28},
 numpages = {6},
 url = {http://doi.acm.org/10.1145/3267851.3267907},
 doi = {10.1145/3267851.3267907},
 acmid = {3267907},
 publisher = {ACM},
 address = {New York, NY, USA},
 keywords = {Human-Agent Negotiation, IAGO Negotiation Platform},
 pdf = {pub/Results_of_the_First_Annual_Human-Agent_League_of_the_Automated_Negotiating_Agents_Competition.pdf}
} 

@INPROCEEDINGS{Cha18,
title={Energy Contract Settlements through Automated Negotiation in Residential Cooperatives},
author={Shantanu Chakraborty and Tim Baarslag and Michael Kaisers},
booktitle={2018 IEEE International Conference on Communications, Control, and Computing Technologies for Smart Grids (SmartGridComm)},
  organization={IEEE},
year={2018},
pages={1-6},
abstract={This paper presents an automated peer-to-peer (P2P) negotiation strategy for settling energy contracts among prosumers in a Residential Energy Cooperative (REC) considering heterogeneous prosumer preferences. The heterogeneity arises from prosumers' evaluation of energy contracts through multiple societal and environmental criteria and the prosumers' private preferences over those criteria. The prosumers engage in bilateral negotiations with peers to mutually agree on periodical energy contracts/loans that consist of an energy volume to be exchanged at that period and the return time of the exchanged energy. The prosumers keep an ordered preference profile of possible energy contracts by evaluating the contracts from their own valuations on the entailed criteria, and iteratively offer the peers contracts until an agreement is formed. A prosumer embeds the valuations into a utility function that further considers uncertainties imposed by demand and generation profiles. Empirical evaluation on real demand, generation and storage profiles illustrates that the proposed negotiation based strategy is able to increase the system efficiency (measured by utilitarian social welfare) and fairness (measured by Nash social welfare) over a baseline strategy and an individual flexibility control strategy. We thus elicit system benefits from P2P flexibility exchange already with few agents and without central coordination, providing a simple yet flexible and effective paradigm that may complement existing markets.},
keywords={Contracts;Batteries;Smart grids;Uncertainty;Peer-to-peer computing;Energy exchange;Protocols},
  url = {https://arxiv.org/abs/1807.10978},
doi={10.1109/SmartGridComm.2018.8587537},
month={Oct},
  pdf = {pub/Energy_Contract_Settlements_through_Automated_Negotiation_in_Residential_Cooperatives.pdf}
}

@InProceedings{Pap18,
  author    = {Iliana Pappi and Tim Baarslag and Michael Kaisers and Nikolaos G. Paterakis},
  title     = {An Uncertainty-Aware Online Planning Algorithm for the Sustainable Electrification of Festivals},
  booktitle = {International Conference on Smart Energy Systems and Technologies (SEST 2018)},
  year      = {2018},
  pages={1-6},
  abstract  = {Energy efficient festival electrification can be viewed as a middle-consumption problem, standing between smart household applications and larger commercial consumers. The optimal deployment of different resources, such as local renewable energy production (RES), diesel generators (DG) and energy storage systems (ESS) may bring about significant financial gain for the organizer, and is usually framed as an off-grid or limited grid-connection problem. This makes online planning particularly challenging due to the uncertainty related to the RES production, constraints regarding the operation of the diesel generators and limitations of the grid connection. In this paper a new online planning algorithm based on two-stage stochastic programming is proposed in order to address the aforementioned challenges and provide minimal-cost, uninterrupted, and sustainable electrification of festivals under dynamically priced grid energy. Data based on real festival events are used in order to illustrate the effectiveness of the proposed methodology.},
  doi={10.1109/SEST.2018.8495825},
  keywords  = {energy storage, festival electrification, online planning, renewable energy, stochastic  programming},
  url = {https://homepages.cwi.nl/~baarslag/pub/An_Uncertainty-Aware_Online_Planning_Algorithm_for_the_Sustainable_Electrification_of_Festivals.pdf},
  pdf       = {pub/An_Uncertainty-Aware_Online_Planning_Algorithm_for_the_Sustainable_Electrification_of_Festivals.pdf},
}

@Article{BaarslagERCIM,
  author  = {Tim Baarslag},
  title   = {Computers that negotiate on our behalf},
  journal = {ERCIM News},
  year    = {2018},
  number  = {112},
  pages   = {36--37},
  month   = {January},
  editors = {Jop Bri\"{e}t and Simon Perdrix},
  abstract = {Computers that negotiate on behalf of humans hold great promise for the future and will even become indispensable in emerging application domains such as the smart grid, autonomous driving, and the Internet of Things. An important obstacle is that in many real-life settings, it is impossible to elicit all information necessary to be sensitive to the individual needs and requirements of users. This makes it a lot more challenging for the computer to decide on the right negotiation strategy; however, new methods are being created at CWI that make considerable progress towards solving this problem.},
  pdf     = {pub/Computers_That_Negotiate_On_Our_Behalf.pdf},
}

@article{BaarslagWired,
title = {How would a machine conduct our salary negotiations?},
journal = {Wired},
year = {2017},
publisher={Wired Germany},
url = {https://www.wired.de/collection/tech/ki-ai-kuenstliche-intelligenz-artificial-intelligence-handel}
}

@article{BaarslagScience,
title = {How artificial intelligence could negotiate better deals for humans},
journal = {Science},
year = {2017},
publisher={American Association for the Advancement of Science},
doi = {10.1126/science.aap9309},
url = {http://www.sciencemag.org/news/2017/09/how-artificial-intelligence-could-negotiate-better-deals-humans}
}

@Inbook{BaarslagChallengesVisionary,
  author       = {Tim Baarslag and Michael Kaisers and Enrico H. Gerding and Catholijn M. Jonker and Jonathan Gratch},
  title        = {Computers That Negotiate on Our Behalf: Major Challenges for Self-sufficient, Self-directed, and Interdependent Negotiating Agents},
  booktitle    = {Autonomous Agents and Multiagent Systems: AAMAS 2017 Workshops, Visionary Papers, S{\~a}o Paulo, Brazil, May 8-12, 2017, Revised Selected Papers},
  year         = {2017},
  publisher    = {Springer International Publishing},
  address          = {Cham},
  pages            = {143--163},
  volume           = {10643},
  series       = {Lecture Notes in Computer Science},
  editor           = {Gita Sukthankar and Juan A. Rodr\'{i}guez-Aguilar},
  isbn             = {978-3-319-71679-4},
  doi              = {10.1007/978-3-319-71679-4_10},
  url              = {https://doi.org/10.1007/978-3-319-71679-4_10},
  abstract         = {Computers that negotiate on our behalf hold great promise for the future and will even become indispensable in emerging application domains such as the smart grid, autonomous driving, and the Internet of Things. Much research has thus been expended to create agents that are able to negotiate in an abundance of circumstances. However, up until now, truly autonomous negotiators have rarely been deployed in real-world applications. This paper sizes up current negotiating agents and explores a number of technological, societal and ethical challenges that autonomous negotiation systems are bringing about. The questions we address are: in what sense are these systems autonomous, what has been holding back their further proliferation, and is their spread something we should encourage? We relate the automated negotiation research agenda to dimensions of autonomy and distill three major themes that we believe will propel autonomous negotiation forward: accurate representation, long-term perspective, and user trust. We argue these orthogonal research directions need to be aligned and advanced in unison to sustain tangible progress in the field.},
    pdf                 = {pub/Computers_That_Negotiate_on_Our_Behalf_Major_Challenges_for_Self-sufficient_Self-directed_and_Interdependent_Negotiating_Agents.pdf}
}

@InProceedings{BaarslagChallenges,
  author    = {Tim Baarslag and Michael Kaisers and Enrico H. Gerding and Catholijn M. Jonker and Jonathan Gratch},
  title     = {When will negotiation agents be able to represent us? {T}he challenges and opportunities for autonomous negotiators},
  booktitle = {Proceedings of the Twenty-sixth International Joint Conference on Artificial Intelligence},
  year      = {2017},
  series    = {IJCAI'17},
  abstract  = {Computers that negotiate on our behalf hold great promise for the future and will even become indispensable in emerging application domains such as the smart grid and the Internet of Things. Much research has thus been expended to create agents that are able to negotiate in an abundance of circumstances. However, up until now, truly autonomous negotiators have rarely been deployed in real-world applications. This paper sizes up current negotiating agents and explores a number of technological, societal and ethical challenges that autonomous negotiation systems have brought about. The questions we address are: in what sense are these systems autonomous, what has been holding back their further proliferation, and is their spread something we should encourage? We relate the automated negotiation research agenda to dimensions of autonomy and distill three major themes that we believe will propel autonomous negotiation forward: accurate representation, long-term perspective, and user trust. We argue these orthogonal research directions need to be aligned and advanced in unison to sustain tangible progress in the field.},
  location  = {Melbourne, Australia},
  pages     = {4684--4690},
  numpages  = {7},
  doi       = {10.24963/ijcai.2017/653},
  url       = {https://doi.org/10.24963/ijcai.2017/653},
  pdf       = {pub/When_Will_Negotiation_Agents_Be_Able_to_Represent_Us-The_Challenges_and_Opportunities_for_Autonomous_Negotiators.pdf},
}

@InBook{PocketNegotiatorEUMAS,
  pages     = {13--27},
  title     = {An Introduction to the Pocket Negotiator: A General Purpose Negotiation Support System},
  publisher = {Springer International Publishing},
  year      = {2017},
  author    = {Jonker, Catholijn M. and Aydo{\u{g}}an, Reyhan and Baarslag, Tim and Broekens, Joost and Detweiler, Christian A. and Hindriks, Koen V. and Huldtgren, Alina and Pasman, Wouter},
  editor    = {Criado Pacheco, Natalia and Carrascosa, Carlos and Osman, Nardine and Juli{\'a}n Inglada, Vicente},
  volume    = {10207},
  address   = {Cham},
  abstract  = {The Pocket Negotiator (PN) is a negotiation support system developed at TU Delft as a tool for supporting people in bilateral negotiations over multi-issue negotiation problems in arbitrary domains. Users are supported in setting their preferences, estimating those of their opponent, during the bidding phase and sealing the deal. We describe the overall architecture, the essentials of the underlying techniques, the form that support takes during the negotiation phases, and we share evidence of the effectiveness of the Pocket Negotiator.},
  booktitle = {Multi-Agent Systems and Agreement Technologies: 14th European Conference, EUMAS 2016, and 4th International Conference, AT 2016, Valencia, Spain, December 15-16, 2016, Revised Selected Papers},
  doi       = {10.1007/978-3-319-59294-7_2},
  isbn      = {978-3-319-59294-7},
  pdf       = {pub/An_Introduction_to_the_Pocket_Negotiator-A_General_Purpose_Negotiation_Support_System.pdf},
  url       = {http://dx.doi.org/10.1007/978-3-319-59294-7_2},
}

@book{COREDEMA2016,
editor="Aydo{\u{g}}an, Reyhan
and Baarslag, Tim
and Gerding, Enrico
and Jonker, Catholijn M.
and Julian, Vicente
and Sanchez-Anguix, Victor",
bookTitle="Conflict Resolution in Decision Making",
subtitle = "Second International Workshop, COREDEMA 2016, The Hague, The Netherlands, August 29-30, 2016",
series = "Lecture Notes in Artificial Intelligence",
volume = "10238",
edition = "1",
year="2017",
publisher="Springer International Publishing",
address="Cham",
isbn="978-3-319-57285-7",
doi="10.1007/978-3-319-57285-7",
url="http://link.springer.com/content/pdf/10.1007/978-3-319-57285-7.pdf",
numpages = {149}
}

@Article{TeamParetoKAIS,
author="Sanchez-Anguix, Victor
and Aydo{\u{g}}an, Reyhan
and Baarslag, Tim
and Jonker, Catholijn",
title="Bottom-up approaches to achieve Pareto optimal agreements in group decision making",
journal="Knowledge and Information Systems",
year="2019",
month="Jan",
day="08",
abstract="In this article, we introduce a new paradigm to achieve Pareto optimality in group decision-making processes: bottom-up approaches to Pareto optimality. It is based on the idea that, while resolving a conflict in a group, individuals may trust some members more than others; thus, they may be willing to cooperate and share more information with those members. Therefore, one can divide the group into subgroups where more cooperative mechanisms can be formed to reach Pareto optimal outcomes. This is the first work that studies such use of a bottom-up approach to achieve Pareto optimality in conflict resolution in groups. First, we prove that an outcome that is Pareto optimal for subgroups is also Pareto optimal for the group as a whole. Then, we empirically analyze the appropriate conditions and achievable performance when applying bottom-up approaches under a wide variety of scenarios based on real-life datasets. The results show that bottom-up approaches are a viable mechanism to achieve Pareto optimality with applications to group decision-making, negotiation teams, and decision making in open environments.",
issn="0219-3116",
doi="10.1007/s10115-018-01325-y",
url="https://doi.org/10.1007/s10115-018-01325-y"
}



@Inbook{TeamParetoCOREDEMA2016,
author="Sanchez-Anguix, Victor
and Aydo{\u{g}}an, Reyhan
and Baarslag, Tim
and Jonker, Catholijn M.",
editor="Aydo{\u{g}}an, Reyhan
and Baarslag, Tim
and Gerding, Enrico
and Jonker, Catholijn M.
and Julian, Vicente
and Sanchez-Anguix, Victor",
title="Can We Reach Pareto Optimal Outcomes Using Bottom-Up Approaches?",
bookTitle="Conflict Resolution in Decision Making: Second International Workshop, COREDEMA 2016, The Hague, The Netherlands, August 29-30, 2016, Revised Selected Papers",
year="2017",
month={Apr},
publisher="Springer International Publishing",
address="Cham",
pages="19--35",
isbn="978-3-319-57285-7",
doi="10.1007/978-3-319-57285-7\_2",
url="https://link.springer.com/content/pdf/10.1007/978-3-319-57285-7\_2.pdf",
abstract = {Classically, disciplines like negotiation and decision making have focused on reaching Pareto optimal solutions due to its stability and efficiency properties. Despite the fact that many practical and theoretical algorithms have successfully attempted to provide Pareto optimal solutions, they have focused on attempting to reach Pareto Optimality using horizontal approaches, where optimality is calculated taking into account every participant at the same time. Sometimes, this may prove to be a difficult task (e.g., conflict, mistrust, no information sharing, etc.). In this paper, we explore the possibility of achieving Pareto Optimal outcomes in a group by using a bottom-up approach: discovering Pareto optimal outcomes by interacting in subgroups. We analytically show that the set of Pareto optimal outcomes in a group covers the Pareto optimal outcomes within its subgroups. This theoretical finding can be applied in a variety of scenarios such as negotiation teams, multi-party negotiation, and team formation to social recommendation. Additionally, we empirically test the validity and practicality of this proof in a variety of decision making domains and analyze the usability of this proof in practical situations.},
keywords = {Pareto optimality, Agreement technologies, Group decision making, Multi-agent systems, Artificial intelligence},
pdf = {pub/Can_We_Reach_Pareto_Optimal_Outcomes_Using_Bottom-up_approaches.pdf}
}


@INPROCEEDINGS{ANACAAAI,
  title={Automated Negotiating Agents Competition {(ANAC)}},
  author={Jonker, Catholijn M. and Aydo{\u{g}}an, Reyhan and Baarslag, Tim and Fujita, Katsuhide and Ito, Takayuki and Hindriks, Koen},
  booktitle = {Proceedings of the Thirty-First AAAI Conference on Artificial Intelligence and Twenty-Ninth Innovative Applications of Artificial Intelligence Conference},
  url = {http://www.aaai.org/ocs/index.php/AAAI/AAAI17/paper/download/14745/14021},
  abstract = {The annual International Automated Negotiating Agents Competition (ANAC) is used by the automated negotiation research community to benchmark and evaluate its work andto challenge itself. The benchmark problems and evaluation results and the protocols and strategies developed are available to the wider research community.},
  keywords = {benchmark, competition, automated negotiation, protocol, profile},
  pages = {5070-5072},
  month = {Feb},
  year={2017},
  pdf={pub/Automated_Negotiating_Agents_Competition_ANAC.pdf}
}

@Article{HeidelbergLaureateForum,
  author     = {Begoli, Edmon and Schlegel, Vincent and Atiyah, Michael and Adeyemo, Praise and Baarslag, Tim},
  title      = {The {Heidelberg Laureate Forum} on the Moving Frontier Between Mathematics and Computer Science},
  journal    = {XRDS},
  year       = {2017},
  volume     = {23},
  number     = {3},
  pages      = {46-49},
  month      = apr,
  abstract   = {Young and early-career researchers at the 2016 Heidelberg Laureate Forum discuss how the frontier between mathematics and computer science is shifting, what the future promises, and the implications the frontier's shape and dynamics will have on both fields.},
  acmid      = {3055143},
  address    = {New York, NY, USA},
  doi        = {10.1145/3055143},
  issn       = {1528-4972},
  issue_date = {Spring 2017},
  numpages   = {4},
  pdf        = {pub/The_Heidelberg_Laureate_Forum_on_the_Moving_Frontier_Between_Mathematics_and_Computer_Science.pdf},
  publisher  = {ACM},
  url        = {http://doi.acm.org/10.1145/3055143},
}

@incollection{ANAC2015,
  title={The Sixth Automated Negotiating Agents Competition ({ANAC} 2015)},
  author={Fujita, Katsuhide and Aydo{\u{g}}an, Reyhan and Baarslag, Tim and Hindriks, Koen and Ito, Takayuki and Jonker, Catholijn},
  booktitle={Modern Approaches to Agent-based Complex Automated Negotiation},
  abstract = {In May 2015, we organized the Sixth International Automated Negotiating Agents Competition (ANAC 2015) in conjunction with AAMAS 2015. ANAC is an international competition that challenges researchers to develop a successful automated negotiator for scenarios where there is incomplete information about the opponent. One of the goals of this competition is to help steer the research in the area of multi-issue negotiations, and to encourage the design of generic negotiating agents that are able to operate in a variety of scenarios. 24 teams from 9 different institutes competed in ANAC 2015. This chapter describes the participating agents and the setup of the tournament, including the different negotiation scenarios that were used in the competition. We report on the results of the qualifying and final round of the tournament.},
  pages={139--151},
  year={2017},
  volume={674},
  publisher={Springer},
  isbn={978-3-319-51563-2},
  issn={1860-949X},
  doi={10.1007/978-3-319-51563-2\_9},
  url={http://dx.doi.org/10.1007/978-3-319-51563-2\_9},
  pdf={pub/The_Sixth_Automated_Negotiating_Agents_Competition_ANAC_2015.pdf}
}

@InProceedings{BaarslagNegotiationAgentForPermissionManagement,
  author    = {Baarslag, Tim and Alan, Alper T. and Gomer, Richard and Alam, Mudasser and Perera, Charith and Gerding, Enrico H. and Schraefel, M.C.},
  title     = {An Automated Negotiation Agent for Permission Management},
  booktitle = {Proceedings of the 2017 International Conference on Autonomous Agents and Multi-agent Systems},
  year      = {2017},
  series    = {AAMAS '17},
  location = {Sao Paulo, Brazil},
  publisher = {International Foundation for Autonomous Agents and Multiagent Systems},
  address = {Richland, SC},
  abstract  = {The digital economy is based on data sharing yet citizens have little control about how their personal data is being used. While data management during web and app-based use is already a challenge, as the Internet of Things (IoT) scales up, the number of devices accessing and requiring personal data will go beyond what a person can manually assess in terms of data access requests. Therefore, new approaches are needed for managing privacy preferences at scale and providing active consent around data sharing that can improve fidelity of operation in alignment with user intent. To address this challenge, we introduce a novel agent-based approach to negotiate the permission to exchange private data between users and services. Our agent negotiates based on learned  preferences from actual users. To evaluate our agent-based approach, we developed an experimental tool to run on people's own smartphones, where users were asked to share their private, real data (e.g. photos, contacts, etc) under various conditions. The agent autonomously negotiates potential agreements for the user, which they can refine by manually continuing the negotiation. The agent learns from these interactions and updates the user model in subsequent interactions. We find that the agent is able to effectively capture the preferences and negotiate on the user's behalf but, surprisingly, does not reduce user engagement with the system. Understanding how interaction interplays with agent-based automation is a key component to successful deployment of negotiating agents in real-life settings and within the IoT context in particular.},
  keywords  = {Automated negotiation, Negotiation agent, Privacy, Permissions, Mobile apps, Negotiation cost, Partial offers, Preference learning},
  pages = {380-390},
  acmid = {3091184},
  numpages  = {11},
  url = {http://dl.acm.org/citation.cfm?id=3091125.3091184},
  pdf       = {pub/An_Automated_Negotiation_Agent_for_Permission_Management.pdf},
}

@InProceedings{BaarslagValueOfInformation,
  author    = {Baarslag, Tim and Kaisers, Michael},
  title     = {The Value of Information in Automated Negotiation: A Decision Model for Eliciting User Preferences},
  booktitle = {Proceedings of the 16th Conference on Autonomous Agents and MultiAgent Systems},
  year      = {2017},
  series    = {AAMAS '17},
  location = {Sao Paulo, Brazil},
  publisher = {International Foundation for Autonomous Agents and Multiagent Systems},
  address = {Richland, SC},
  abstract  = {Consider an agent that can autonomously negotiate and coordinate with others in our stead, to reach outcomes and agreements in our interest. Such automated negotiation agents are already common practice in areas such as high frequency trading, and are now finding applications in domains closer to home, which involve not only mere financial optimizations but balanced tradeoffs between multiple issues, such as cost and convenience. As a simple example, a smart thermostat controlling a heat pump could provide demand response to the electricity grid if the inconvenience is offset by the grid relieve incentives. In such situations, the agent represents a user with individual and a priori unknown preferences, which are costly to elicit due to the user bother this incurs. Therefore, the agent needs to strike a  balance between increasing the user model accuracy and the inconvenience caused by interacting with the user. To do so, we require a tractable metric for the value of information in an ensuing negotiation, which until now has not been available. In this paper, we propose a decision model that finds the point of diminishing returns for improving the model of user preferences with costly queries. We present a reasoning framework to derive this metric, and show a myopically optimal and tractable stopping criterion for querying the user before a fixed number of negotiation rounds. Our method provides an extensible basis for interactive negotiation agents to evaluate which questions are worth posing given the marginal utility expected to arise from more accurate beliefs.},
  keywords = {automated negotiation, negotiation agent, optimal query, preference elicitation, uncertain preferences, user preferences, value of information},
  pages = {391-400},
  numpages  = {10},
  url = {http://dl.acm.org/citation.cfm?id=3091125.3091185},
  acmid = {3091185},
  pdf       = {pub/The_Value_of_Information_in_Automated_Negotiation_A_Decision_Model_for_Eliciting_User_Preferences.pdf},
}


@Article{BaarslagOMSurvey,
  author    = {Tim Baarslag and Mark J.C. Hendrikx and Koen V. Hindriks and Catholijn M. Jonker},
  title     = {Learning about the opponent in automated bilateral negotiation: a comprehensive survey of opponent modeling techniques},
  journal   = {Autonomous Agents and Multi-Agent Systems},
  year      = {2016},
  volume    = {30},
  number    = {5},
  pages     = {849--898},
  abstract  = {A negotiation between agents is typically an incomplete information game, where the agents initially do not know their opponent's preferences or strategy. This poses a challenge, as efficient and effective negotiation requires the bidding agent to take the other's wishes and future behavior into account when deciding on a proposal. Therefore, in order to reach better and earlier agreements, an agent can apply learning techniques to construct a model of the opponent. There is a mature body of research in negotiation that focuses on modeling the opponent, but there exists no recent survey of commonly used opponent modeling techniques. This work aims to advance and integrate knowledge of the field by providing a comprehensive survey of currently existing opponent models in a bilateral negotiation setting. We discuss all possible ways opponent modeling has been used to benefit agents so far, and we introduce a taxonomy of currently existing opponent models based on their underlying learning techniques. We also present techniques to measure the success of opponent models and provide guidelines for deciding on the appropriate performance measures for every opponent model type in our taxonomy.},
  doi       = {10.1007/s10458-015-9309-1},
  file      = {:Learning about the opponent in automated bilateral negotiation - a comprehensive survey of opponent modeling techniques.pdf:PDF},
  issn      = {1573-7454},
  keywords  = {Negotiation, Software agents, Opponent model, Learning techniques, Automated negotiation, Opponent modeling, Machine learning, Survey},
  language  = {English},
  pdf       = {pub/Learning_about_the_opponent_in_automated_bilateral_negotiation-a_comprehensive_survey_of_opponent_modeling_techniques.pdf},
  publisher = {Springer US},
  url       = {http://dx.doi.org/10.1007/s10458-015-9309-1},
  link = {http://rdcu.be/ofJ8}
}

@Article{Perera2016IoTDatabox,
  author    = {Perera, Charith and Wakenshaw, Susan Y. L. and Baarslag, Tim and Haddadi, Hamed and Bandara, Arosha K. and Mortier, Richard and Crabtree, Andy and Ng, Irene C. L. and McAuley, Derek and Crowcroft, Jon},
  title     = {Valorising the {IoT} Databox: creating value for everyone},
  journal   = {Transactions on Emerging Telecommunications Technologies},
  year      = {2017},
  abstract  = {The Internet of Things is expected to generate large amounts of heterogeneous data from diverse sources including physical sensors, user devices and social media platforms. Over the last few years, significant attention has been focused on personal data, particularly data generated by smart wearable and smart home devices. Making personal data available for access and trade is expected to become a part of the data-driven digital economy. In this position paper, we review the research challenges in building personal Databoxes that hold personal data and enable data access by other parties and potentially thus sharing of data with other parties. These Databoxes are expected to become a core part of future data marketplaces.},
  doi       = {10.1002/ett.3125},
  issn      = {2161-3915},
  volume = {28},
  number = {1},
  pages = {1-17},
  pdf       = {pub/Valorising_the_IoT_Databox-Creating_Value_for_Everyone.pdf},
  publisher = {John Wiley \& Sons, Ltd},
  url       = {http://dx.doi.org/10.1002/ett.3125},
}

@Book{BaarslagSpringerTheses,
  title     = {Exploring the Strategy Space of Negotiating Agents: A Framework for Bidding, Learning and Accepting in Automated Negotiation},
  publisher = {Springer International Publishing},
  year      = {2016},
  author    = {Tim Baarslag},
  series    = {Springer Theses: Recognizing Outstanding Ph.D. Research},
  abstract  = {This book reports on an outstanding thesis that has significantly advanced the state-of-the-art in the area of automated negotiation. It gives new practical and theoretical insights into the design and evaluation of automated negotiators. It describes an innovative negotiating agent framework that enables systematic exploration of the space of possible negotiation strategies by recombining different agent components. Using this framework, new and effective ways are formulated for an agent to learn, bid, and accept during a negotiation. The findings have been evaluated in four annual instantiations of the International Automated Negotiating Agents Competition (ANAC), the results of which are also outlined here. The book also describes several methodologies for evaluating and comparing negotiation strategies and components, with a special emphasis on performance and accuracy measures.},
  doi       = {10.1007/978-3-319-28243-5},
  isbn      = {978-3-319-28242-8},
  oclc          = {985062026},
  pdf       = {http://dx.doi.org/10.1007/978-3-319-28243-5},
  url       = {http://dx.doi.org/10.1007/978-3-319-28243-5},
}

@InProceedings{TruongSchedulingApplianceUsage,
  author    = {Ngoc Cuong Truong and Tim Baarslag and Gopal Ramchurn and Long Tran-Thanh},
  title     = {Interactive scheduling of appliance usage in the home},
  booktitle = {The 25th International Joint Conference on Artificial Intelligence},
  year      = {2016},
  month     = {June},
  publisher = {AAAI Press},
  abstract  = {We address the problem of recommending an appliance usage schedule to the homeowner which balances between maximising total savings and maintaining sufficient user convenience. An important challenge within this problem is how to elicit the the user preferences with low intrusiveness, in order to identify new schedules with high cost savings, that still lies within the user's comfort zone. To tackle this problem we propose iDR, an interactive system for generating personalised appliance usage scheduling recommendations that maximise savings and convenience with minimal intrusiveness. In particular, our system learns when to stop interacting with the user during the preference elicitation process, in order to keep the bother cost (e.g., the amount of time the user spends, or the cognitive cost of interacting) minimal. We demonstrate through extensive empirical evaluation on real-world data that our approach improves savings by up to 35\%, while maintaining a significantly lower bother cost, compared to state-of the-art benchmarks.},
  file      = {:Interactive Scheduling of Appliance Usage in the Home.pdf:PDF},
  pdf       = {pub/Interactive_scheduling_of_appliance_usage_in_the_home.pdf},
  url       = {http://eprints.soton.ac.uk/396670/},
}

@InProceedings{ChenRobotSearch,
  author    = {Shaofei Chen and Tim Baarslag and Dengji Zhao and Jing Chen and Lincheng Shen},
  title     = {A polynomial time optimal algorithm for robot-human search under uncertainty},
  booktitle = {Proceedings of the Twenty-Fifth International Joint Conference on Artificial Intelligence},
  series = {IJCAI'16},
  pages = {819-825},
  numpages = {7},
  isbn = {978-1-57735-770-4},
  year      = {2016},
  acmid = {3060735},
  month     = {July},
  publisher = {AAAI Press},
  location = {New York, USA},
  abstract  = {This paper studies a search problem involving a robot that is searching for a certain item in an uncertain environment (e.g., searching minerals on the moon) that allows only limited interaction with humans. The uncertainty of the environment comes from the rewards of undiscovered items and the availability of costly human help. The goal of the robot is to maximize the reward of the items found while minimising the search costs. We show that this search problem is polynomially solvable with a novel integration of the human help, which has not been studied in the literature before. Furthermore, we empirically evaluate our solution with simulations and show that it significantly outperforms several benchmark approaches.},
  file      = {:A Polynomial Time Optimal Algorithm for Robot-Human Search under Uncertainty.pdf:PDF},
  pdf       = {pub/A_polynomial_time_optimal_algorithm_for_robot-human_search_under_uncertainty.pdf},
  url = {http://dl.acm.org/citation.cfm?id=3060621.3060735},
}

@InProceedings{BaarslagNegotiationAsAnInteractionMechanism,
  author    = {Baarslag, Tim and Alan, Alper T. and Gomer, Richard C. and Liccardi, Ilaria and Marreiros, Helia and Gerding, Enrico H. and Schraefel, M.C.},
  title     = {Negotiation As an Interaction Mechanism for Deciding App Permissions},
  booktitle = {Proceedings of the 2016 CHI Conference: Extended Abstracts on Human Factors in Computing Systems},
  year      = {2016},
  series    = {CHI EA '16},
  pages     = {2012--2019},
  address   = {New York, NY, USA},
  publisher = {ACM},
  abstract  = {On the Android platform, apps make use of personal data as part of their business model, trading location, contacts, photos and more for app use. Few people are particularly aware of the permission settings or make changes to them. We hypothesize that both the difficulty in checking permission settings for all apps on a device, along with the lack of flexibility in deciding what happens to one's data, makes the perceived cost to protect one's privacy too high. In this paper, we present the preliminary results of a study that explores what happens when permission settings are more discretional at install time. We present the results of a pilot experiment, in which we ask users to negotiate which data they are happy to share, and we show that this results in higher user satisfaction than the typical take-it-or-leave-it setting. Our preliminary findings suggest negotiating consent is a powerful interaction mechanism that engages users and can enable them to strike a balance between privacy and pricing concerns.},
  acmid     = {2892340},
  doi       = {10.1145/2851581.2892340},
  file      = {:Negotiation as an Interaction Mechanism for Deciding App Permissions.pdf:PDF},
  isbn      = {978-1-4503-4082-3},
  keywords  = {interaction, mobile, negotiation, permissions, privacy},
  location  = {Santa Clara, California, USA},
  numpages  = {8},
  pdf       = {pub/Negotiation_As_an_Interaction_Mechanism_for_Deciding_App_Permissions.pdf},
  url       = {http://doi.acm.org/10.1145/2851581.2892340},
}

@InBook{ANAC2014Baseline,
  author    = {Reyhan Aydo{\u{g}}an and Tim Baarslag and Catholijn M. Jonker and Katsuhide Fujita and Takayuki Ito and Rafik Hadfi and Kohei Hayakawa},
  title     = {A Baseline for Non-Linear Bilateral Negotiations: The full results of the agents competing in {ANAC} 2014},
  year      = {2016},
  abstract  = {In the past few years, there is a growing interest in automated negotiation in which software agents facilitate negotiation on behalf of their users and try to reach joint agreements. The potential value of developing such mechanisms becomes enormous when negotiation domain is too complex for humans to find agreements (e.g. e-commerce) and when software components need to reach agreements to work together (e.g. web-service composition). Here, one of the major challenges is to design agents that are able to deal with incomplete information about their opponents in negotiation as well as to effectively negotiate on their users? behalves. To facilitate the research in this field, an automated negotiating agent competition has been organized yearly. This paper introduces the research challenges in Automated Negotiating Agent Competition (ANAC) 2014 and explains the competition set up and results. Furthermore, a detailed analysis of the best performing five agents has been examined.},
  booktitle = {Intelligent Computational Systems: A Multi-Disciplinary Perspective},
  pdf       = {pub/A_Baseline_for_Non-Linear_Bilateral_Negotiations-The_full_results_of_the_agents_competing_in_ANAC_2014.pdf},
  publisher = {Bentham Science Publishers},
  series    = {Frontiers in Artificial Intelligence},
  url       = {http://eprints.soton.ac.uk/399235/},
}

@InBook{ANAC2014,
  title     = {The Fifth Automated Negotiating Agents Competition ({ANAC} 2014)},
  publisher = {Springer International Publishing},
  year      = {2016},
  author    = {Fujita, Katsuhide and Aydo{\u{g}}an, Reyhan and Baarslag, Tim and Ito, Takayuki and Jonker, Catholijn},
  editor    = {Fukuta, Naoki and Ito, Takayuki and Zhang, Minjie and Fujita, Katsuhide and Robu, Valentin},
  address   = {Cham},
  abstract  = {In May 2014, we organized the Fifth International Automated Negotiating Agents Competition (ANAC 2014) in conjunction with AAMAS 2014. ANAC is an international competition that challenges researchers to develop a successful automated negotiator for scenarios where there is incomplete information about the opponent. One of the goals of this competition is to help steer the research in the area of bilateral multi-issue negotiations, and to encourage the design of generic negotiating agents that are able to operate in a variety of scenarios. 21 teams from 13 different institutes competed in ANAC 2014. This chapter describes the participating agents and the setup of the tournament, including the different negotiation scenarios that were used in the competition. We report on the results of the qualifying and final round of the tournament.},
  booktitle = {Recent Advances in Agent-based Complex Automated Negotiation},
  volume = {638},
  pages     = {211--224},
  doi       = {10.1007/978-3-319-30307-9\_13},
  isbn      = {978-3-319-30307-9},
  pdf       = {pub/The_Fifth_Automated_Negotiating_Agents_Competition_ANAC_2014.pdf},
  url       = {http://dx.doi.org/10.1007/978-3-319-30307-9\_13},
}

@InProceedings{BaarslagOMSurveyAAMAS,
  author    = {Tim Baarslag and Mark J.C. Hendrikx and Koen V. Hindriks and Catholijn M. Jonker},
  title     = {A Survey of Opponent Modeling Techniques in Automated Negotiation},
  booktitle = {Proceedings of the 2016 International Conference on Autonomous Agents and Multi-agent Systems},
  year      = {2016},
  series    = {AAMAS '16},
  pages     = {575--576},
  address   = {Richland, SC},
  publisher = {International Foundation for Autonomous Agents and Multiagent Systems},
  abstract  = {Negotiation is a process in which parties interact to settle a mutual concern to improve their status quo.  Traditionally, negotiation is a necessary, but time-consuming and expensive activity.  Therefore, in the last two decades, there has been a growing interest in the automation of negotiation. One of the key challenges for a successful negotiation is that usually only limited information is available about the opponent.  Although sharing private information can result in mutual gains, negotiators often avoid this to prevent exploitation.  This problem can be partially overcome by deriving information from the opponent's actions. Exploiting this information to learn aspects of the opponent is called opponent modeling. Creating an accurate opponent model is a key factor in improving the quality of the outcome and can further increase the benefits of automated negotiation. Despite the advantages of opponent modeling and two decades of research, there is no recent study that provides an overview of the field. Therefore, in order to stimulate the development of efficient future opponent models, and to outline a research agenda, we provide an overview of existing opponent models in bilateral negotiation. As our main contributions, we classify opponent models using a comprehensive taxonomy and provide recommendations on how to select the best model depending on the negotiation setting.},
  acmid     = {2937008},
  isbn      = {978-1-4503-4239-1},
  keywords  = {automated negotiation, learning techniques, machine learning, negotiation, opponent model, opponent modeling, software agents, survey},
  location  = {Singapore, Singapore},
  numpages  = {2},
  pdf       = {pub/A_survey_of_opponent_modeling_techniques_in_automated_negotiation.pdf},
  url       = {http://dl.acm.org/citation.cfm?id=2936924.2937008},
}

@InProceedings{BaarslagSimultaneousSearch,
  author    = {Tim Baarslag and Enrico H. Gerding and Reyhan Aydo{\u{g}}an and M.C. Schraefel},
  title     = {Optimal Negotiation Decision Functions in Time-Sensitive Domains},
  booktitle = {2015 IEEE/WIC/ACM International Joint Conferences on Web Intelligence (WI) and Intelligent Agent Technologies (IAT)},
  year      = {2015},
  volume    = {2},
  pages     = {190-197},
  month     = {Dec},
  abstract  = {The last two decades have seen a growing interest in automated agents that are able to negotiate on behalf of human negotiators in a wide variety of negotiation domains. One key aspect of a successful negotiating agent is its ability to make appropriate concessions at the right time, especially when there are costs associated with the duration of the negotiation. However, so far, there is no fundamental approach on how much to concede at every stage of the negotiation in such time-sensitive domains. We introduce an efficient solution based on simultaneous search, which is able to select the optimal sequence of offers that maximizes expected payoff, given the agent's beliefs about the opponent. To this end, we show that our approach is consistent with known theoretical results and we demonstrate both its effectiveness and natural properties by applying it to a number of typical negotiation scenarios. Finally, we show in a number of experiments that our solution outperforms other state of the art strategy benchmarks.},
  doi       = {10.1109/WI-IAT.2015.161},
  keywords  = {multi-agent systems;negotiation support systems;automated agents;negotiating agent;optimal negotiation decision functions;simultaneous search;time-sensitive domains;Cost function;Electronic mail;Force;Games;Intelligent agents;Planning;Uncertainty;Automated negotiation;Bidding strategy;Cascade model;Concessions;Cost;Costly negotiation;Decision function;Distributive bargaining;Integrative bargaining;Negotiation;Optimal offers;Simultaneous search;Time-sensitive},
  pdf       = {pub/Optimal_Negotiation_Decision_Functions_in_Time-Sensitive_Domains.pdf},
  url       = {http://dx.doi.org/10.1109/WI-IAT.2015.161},
}

@Article{BaarslagANAC2010-2015,
  author    = {Tim Baarslag and Reyhan Aydo{\u{g}}an and Koen V. Hindriks and Katsuhide Fuijita and Takayuki Ito and Catholijn M. Jonker},
  title     = {The Automated Negotiating Agents Competition, 2010-2015},
  journal   = {AI Magazine},
  year      = {2015},
  volume    = {36},
  number    = {4},
  pages     = {115-118},
  month     = {12/2015},
  abstract  = {The Automated Negotiating Agents Competition is an international event that, since 2010, has contributed to the evaluation and development of new techniques and benchmarks for improving the state of the art in automated multi-issue negotiation. A key objective of the competition has been to analyze and search the design space of negotiating agents for agents that are able to operate effectively across a variety of domains. The competition is a valuable tool for studying important aspects of negotiation including profiles and domains, opponent learning, strategies, and bilateral and multilateral protocols. Two of the challenges that remain are how to develop argumentation-based negotiation agents that, in addition to making offers, can inform and argue to obtain an acceptable agreement for both parties; and how to create agents that can negotiate in a human fashion.},
  pdf       = {pub/The_Automated_Negotiating_Agents_Competition-2010-2015.pdf},
  publisher = {Association for the Advancement of Artificial Intelligence (AAAI)},
  type      = {Competition report},
  url       = {http://www.aaai.org/ojs/index.php/aimagazine/article/view/2609},
}

@inproceedings{BaarslagNegotiatingMobileAppPermissions,
  title={Negotiating Mobile App Permissions},
  author={Tim Baarslag and Ilaria Liccardi and Enrico H. Gerding and Richard Gomer and M.C. Schraefel},
  booktitle={Amsterdam privacy conference},
  year={2015},
  abstract={We propose a design in which the user can negotiate a mobile app's permissions to access their personal data. For example, users who prefer not to view ads could opt to pay an additional fee for this. However, negotiating with each app might be cumbersome and difficult to achieve by users. Hence, to make this process easier, we propose an approach that uses an agent-based framework that employs software agents to represent users in their privacy negotiation with the app in an automated manner.},
  url = {http://eprints.soton.ac.uk/377378/}
}

@InProceedings{BaarslagPandora,
  author       = {Tim Baarslag and Enrico H. Gerding},
  title        = {Optimal Incremental Preference Elicitation during Negotiation},
  booktitle    = {Proceedings of the Twenty-fourth International Joint Conference on Artificial Intelligence},
  year         = {2015},
  series       = {IJCAI'15},
  pages        = {3--9},
  organization = {AAAI Press},
  abstract     = {The last two decades have seen a growing interest in the development of automated agents that are able to negotiate on the user's behalf. When representing a user in a negotiation, it is essential for the agent to understand the user's preferences, without exposing them to elicitation fatigue. To this end, we propose a new model in which a negotiating agent may incrementally elicit the user's preference during the negotiation.  We introduce an optimal elicitation strategy that decides, at every stage of the negotiation, how much additional user information to extract at a certain cost. Finally, we demonstrate the effectiveness of our approach by combining our policy with well-known negotiation strategies and show that it significantly outperforms other elicitation strategies.},
  acmid        = {2832250},
  isbn         = {978-1-57735-738-4},
  location     = {Buenos Aires, Argentina},
  numpages     = {7},
  pdf          = {pub/Optimal_Incremental_Preference_Elicitation_during_Negotiation.pdf},
  url          = {http://dl.acm.org/citation.cfm?id=2832249.2832250},
}

@inproceedings{BaarslagPandoraAMEC,
  title={Optimal Incremental Preference Elicitation during Negotiation},
  author={Tim Baarslag and Enrico H. Gerding},
  booktitle={17th International Workshop on Agent-Mediated Electronic Commerce and Trading Agents Design and Analysis},
  year={2015},
  url = {http://dl.acm.org/citation.cfm?id=2832249.2832250}
}

@PHDTHESIS{BaarslagThesis,
  author = {Tim Baarslag},
  title = {What to Bid and When to Stop},
  school = {Delft University of Technology},
  year = {2014},
  month = {Sep},
  isbn = {978-94-6186-305-8},
  doi = {10.4233/uuid:3df6e234-a7c1-4dbe-9eb9-baadabc04bca},
  url = {http://dx.doi.org/10.4233/uuid:3df6e234-a7c1-4dbe-9eb9-baadabc04bca},
  type = {Dissertation},
  pdf = {pub/What_to_Bid_and_When_to_Stop.pdf},
  abstract = {Negotiation is an important activity in human society, and is studied by various disciplines, ranging from economics and game theory, to electronic commerce, social psychology, and artificial intelligence. Traditionally, negotiation is a necessary, but also time-consuming and expensive activity. Therefore, in the last decades there has been a large interest in the automation of negotiation, for example in the setting of e-commerce. This interest is fueled by the promise of automated agents eventually being able to negotiate on behalf of human negotiators. Every year, automated negotiation agents are improving in various ways, and there is now a large body of negotiation strategies available, all with their unique strengths and weaknesses. For example, some agents are able to predict the opponent's preferences very well, while others focus more on having a sophisticated bidding strategy. The problem however, is that there is little incremental improvement in agent design, as the agents are tested in varying negotiation settings, using a diverse set of performance measures. This makes it very difficult to meaningfully compare the agents, let alone their underlying techniques. As a result, we lack a reliable way to pinpoint the most effective components in a negotiating agent. There are two major advantages of distinguishing between the different components of a negotiating agent's strategy: first, it allows the study of the behavior and performance of the components in isolation. For example, it becomes possible to compare the preference learning component of all agents, and to identify the best among them. Second, we can proceed to mix and match different components to create new negotiation strategies., e.g.: replacing the preference learning technique of an agent and then examining whether this makes a difference. Such a procedure enables us to combine the individual components to systematically explore the space of possible negotiation strategies. To develop a compositional approach to evaluate and combine the components, we identify structure in most agent designs by introducing the BOA architecture, in which we can develop and integrate the different components of a negotiating agent. We identify three main components of a general negotiation strategy; namely a bidding strategy (B), possibly an opponent model (O), and an acceptance strategy (A). The bidding strategy considers what concessions it deems appropriate given its own preferences, and takes the opponent into account by using an opponent model. The acceptance strategy decides whether offers proposed by the opponent should be accepted. The BOA architecture is integrated into a generic negotiation environment called Genius, which is a software environment for designing and evaluating negotiation strategies. To explore the negotiation strategy space of the negotiation research community, we amend the Genius repository with various existing agents and scenarios from literature. Additionally, we organize a yearly international negotiation competition (ANAC) to harvest even more strategies and scenarios. ANAC also acts as an evaluation tool for negotiation strategies, and encourages the design of negotiation strategies and scenarios. We re-implement agents from literature and ANAC and decouple them to fit into the BOA architecture without introducing any changes in their behavior. For each of the three components, we manage to find and analyze the best ones for specific cases, as described below. We show that the BOA framework leads to significant improvements in agent design by wining ANAC 2013, which had 19 participating teams from 8 international institutions, with an agent that is designed using the BOA framework and is informed by a preliminary analysis of the different components. In every negotiation, one of the negotiating parties must accept an offer to reach an agreement. Therefore, it is important that a negotiator employs a proficient mechanism to decide under which conditions to accept. When contemplating whether to accept an offer, the agent is faced with the acceptance dilemma: accepting the offer may be suboptimal, as better offers may still be presented before time runs out. On the other hand, accepting too late may prevent an agreement from being reached, resulting in a break off with no gain for either party. We classify and compare state-of-the-art generic acceptance conditions. We propose new acceptance strategies and we demonstrate that they outperform the other conditions. We also provide insight into why some conditions work better than others and investigate correlations between the properties of the negotiation scenario and the efficacy of acceptance conditions. Later, we adopt a more principled approach by applying optimal stopping theory to calculate the optimal decision on the acceptance of an offer. We approach the decision of whether to accept as a sequential decision problem, by modeling the bids received as a stochastic process. We determine the optimal acceptance policies for particular opponent classes and we present an approach to estimate the expected range of offers when the type of opponent is unknown. We show that the proposed approach is able to find the optimal time to accept, and improves upon all existing acceptance strategies. Another principal component of a negotiating agent's strategy is its ability to take the opponent's preferences into account. The quality of an opponent model can be measured in two different ways. One is to use the agent's performance as a benchmark for the model's quality. We evaluate and compare the performance of a selection of state-of-the-art opponent modeling techniques in negotiation. We provide an overview of the factors influencing the quality of a model and we analyze how the performance of opponent models depends on the negotiation setting. We identify a class of simple and surprisingly effective opponent modeling techniques that did not receive much previous attention in literature. The other way to measure the quality of an opponent model is to directly evaluate its accuracy by using similarity measures. We review all methods to measure the accuracy of an opponent model and we then analyze how changes in accuracy translate into performance differences. Moreover, we pinpoint the best predictors for good performance. This leads to new insights concerning how to construct an opponent model, and what we need to measure when optimizing performance. Finally, we take two different approaches to gain more insight into effective bidding strategies. We present a new classification method for negotiation strategies, based on their pattern of concession making against different kinds of opponents. We apply this technique to classify some well-known negotiating strategies, and we formulate guidelines on how agents should bid in order to be successful, which gives insight into the bidding strategy space of negotiating agents. Furthermore, we apply optimal stopping theory again, this time to find the concessions that maximize utility for the bidder against particular opponents. We show there is an interesting connection between optimal bidding and optimal acceptance strategies, in the sense that they are mirrored versions of each other. Lastly, after analyzing all components separately, we put the pieces back together again. We take all BOA components accumulated so far, including the best ones, and combine them all together to explore the space of negotiation strategies. We compute the contribution of each component to the overall negotiation result, and we study the interaction between components. We find that combining the best agent components indeed makes the strongest agents. This shows that the component-based view of the BOA architecture not only provides a useful basis for developing negotiating agents but also provides a useful analytical tool. By varying the BOA components we are able to demonstrate the contribution of each component to the negotiation result, and thus analyze the significance of each. The bidding strategy is by far the most important to consider, followed by the acceptance conditions and finally followed by the opponent model. Our results validate the analytical approach of the BOA framework to first optimize the individual components, and then to recombine them into a negotiating agent.}
}

@Article{Baarslag12Genius,
  author    = {Raz Lin and Sarit Kraus and Tim Baarslag and Dmytro Tykhonov and Koen V. Hindriks and Catholijn M. Jonker},
  title     = {Genius: An Integrated Environment for Supporting the Design of Generic Automated Negotiators},
  journal   = {Computational Intelligence},
  year      = {2014},
  volume    = {30},
  number    = {1},
  pages     = {48--70},
  abstract  = {The design of automated negotiators has been the focus of abundant
        research in recent years. However, due to difficulties involved in
        creating generalized agents that can negotiate in several domains
        and against human counterparts, many automated negotiators are domain
        specific and their behavior cannot be generalized for other domains.
        Some of these difficulties arise from the differences inherent within
        the domains, the need to understand and learn negotiators' diverse
        preferences concerning issues of the domain, and the different strategies
        negotiators can undertake. In this paper we present a system that
        enables alleviation of the difficulties in the design process of
        general automated negotiators termed Genius, a General Environment
        for Negotiation with Intelligent multi-purpose Usage Simulation.
        With the constant introduction of new domains, e-commerce and other
        applications, which require automated negotiations, generic automated
        negotiators encompass many benefits and advantages over agents that
        are designed for a specific domain. Based on experiments conducted
        with automated agents designed by human subjects using Genius we
        provide both quantitative and qualitative results to illustrate its
        efficacy. Finally, we also analyze a recent automated bilateral negotiators
        competition that was based on Genius. Our results show the advantages
        and underlying benefits of using Genius and how it can facilitate
        the design of general automated negotiators.},
  doi       = {10.1111/j.1467-8640.2012.00463.x},
  issn      = {1467-8640},
  keywords  = {agents competition, automated negotiation, human/computer interaction, bilateral negotiation},
  pdf       = {pub/Genius-An_Integrated_Environment_for_Supporting_the_Design_of_Generic_Automated_Negotiators.pdf},
  publisher = {Blackwell Publishing Inc},
  url       = {http://dx.doi.org/10.1111/j.1467-8640.2012.00463.x},
}

@Article{Baarslag13DSS,
  author     = {Tim Baarslag and Koen V. Hindriks and Catholijn M. Jonker},
  title      = {Effective Acceptance Conditions in Real-time Automated Negotiation},
  journal    = {Decision Support Systems},
  year       = {2014},
  volume     = {60},
  pages      = {68--77},
  month      = {Apr},
  abstract   = {In every negotiation with a deadline, one of the negotiating parties
        must accept an offer to avoid a break off. As a break off is usually
        an undesirable outcome for both parties, it is important that a negotiator
        employs a proficient mechanism to decide under which conditions to
        accept. When designing such conditions, one is faced with the acceptance
        dilemma: accepting the current offer may be suboptimal, as better
        offers may still be presented before time runs out. On the other
        hand, accepting too late may prevent an agreement from being reached,
        resulting in a break off with no gain for either party. Motivated
        by the challenges of bilateral negotiations between automated agents
        and by the results and insights of the automated negotiating agents
        competition (ANAC), we classify and compare state-of-the-art generic
        acceptance conditions. We perform extensive experiments to compare
        the performance of various acceptance conditions in combination with
        a broad range of bidding strategies and negotiation scenarios. Furthermore
        we propose new acceptance conditions and we demonstrate that they
        outperform the other conditions. We also provide insight into why
        some conditions work better than others and investigate correlations
        between the properties of the negotiation scenario and the efficacy
        of acceptance conditions.},
  acmid      = {2599194},
  address    = {Amsterdam, The Netherlands, The Netherlands},
  doi        = {10.1016/j.dss.2013.05.021},
  issn       = {0167-9236},
  issue_date = {April, 2014},
  keywords   = {Acceptance conditions, Acceptance criteria, Automated negotiation, Real-time bilateral negotiation, When to accept},
  numpages   = {10},
  pdf        = {pub/Effective_Acceptance_Conditions_in_Real-time_Automated_Negotiation.pdf},
  publisher  = {Elsevier Science Publishers B.V.},
  url        = {http://dx.doi.org/10.1016/j.dss.2013.05.021},
}

@INPROCEEDINGS{Baarslag11ICTOpen,
  author = {Tim Baarslag and Koen V. Hindriks and Catholijn M. Jonker},
  title = {Acceptance Conditions in Automated Negotiation},
  booktitle = {Proceedings of ICT.Open 2011},
  year = {2011},
  abstract = {In every negotiation with a deadline, one of the negotiating parties
        has to accept an offer to avoid a break off. A break off is usually
        an undesirable outcome for both parties, therefore it is important
        that a negotiator employs a proficient mechanism to decide under
        which conditions to accept. When designing such conditions one is
        faced with the acceptance dilemma: accepting the current offer may
        be suboptimal, as better offers may still be presented. On the other
        hand, accepting too late may prevent an agreement from being reached,
        resulting in a break off with no gain for either party. Motivated
        by the challenges of bilateral negotiations between automated agents
        and by the results and insights of the automated negotiating agents
        competition (ANAC), we classify and compare state-of-the-art generic
        acceptance conditions. We focus on decoupled acceptance conditions,
        i.e. conditions that do not depend on the bidding strategy that is
        used. We performed extensive experiments to compare the performance
        of acceptance conditions in combination with a broad range of bidding
        strategies and negotiation domains. Furthermore we propose new acceptance
        conditions and we demonstrate that they outperform the other conditions
        that we study. In particular, it is shown that they outperform the
        standard acceptance condition of comparing the current offer with
        the offer the agent is ready to send out. We also provide insight
        in to why some conditions work better than others and investigate
        correlations between the properties of the negotiation environment
        and the efficacy of acceptance conditions.},
  isbn = {978-90-73461-99-4},
  url = {http://ii.tudelft.nl/?q=node/7719},
  location = {Veldhoven, the Netherlands}
}

@InProceedings{Baarslag10ANAC,
  author    = {Baarslag, Tim and Hindriks, Koen V. and Jonker, Catholijn M. and Kraus, Sarit and Lin, Raz},
  title     = {The First Automated Negotiating Agents Competition ({ANAC} 2010)},
  booktitle = {New Trends in Agent-based Complex Automated Negotiations},
  year      = {2012},
  editor    = {Takayuki Ito and Minjie Zhang and Valentin Robu and Shaheen Fatima and Tokuro Matsuo},
  volume    = {383},
  series    = {Studies in Computational Intelligence},
  pages     = {113-135},
  address   = {Berlin, Heidelberg},
  publisher = {Springer-Verlag},
  abstract  = {Motivated by the challenges of bilateral negotiations between people
        and automated agents we organized the first automated negotiating
        agents competition (ANAC 2010). The purpose of the competition is
        to facilitate the research in the area bilateral multi-issue closed
        negotiation. The competition was based on the Genius environment,
        which is a General Environment for Negotiation with Intelligent multi-purpose
        Usage Simulation. The first competition was held in conjunction with
        the Ninth International Conference on Autonomous Agents and Multiagent
        Systems (AAMAS-10) and was comprised of seven teams. This paper presents
        an overview of the competition, as well as general and contrasting
        approaches towards negotiation strategies that were adopted by the
        participants of the competition. Based on analysis in post--tournament
        experiments, the paper also attempts to provide some insights with
        regard to effective approaches towards the design of negotiation
        strategies.},
  doi       = {10.1007/978-3-642-24696-8\_7},
  isbn      = {978-3-642-24695-1},
  pdf       = {pub/The_First_Automated_Negotiating_Agents_Competition_ANAC_2010.pdf},
  url       = {http://dx.doi.org/10.1007/978-3-642-24696-8_7},
}

@INPROCEEDINGS{Baarslag10ANACshort,
  author = {Baarslag, Tim and Hindriks, Koen V. and Jonker, Catholijn M. and Kraus,
        Sarit and Lin, Raz},
  title = {The First Automated Negotiating Agents Competition ({ANAC} 2010)},
  booktitle = {New Trends in Agent-based Complex Automated Negotiations},
  year = {2012},
  pages = {113-135},
  publisher = {Springer-Verlag},
  abstract = {Motivated by the challenges of bilateral negotiations between people
        and automated agents we organized the first automated negotiating
        agents competition (ANAC 2010). The purpose of the competition is
        to facilitate the research in the area bilateral multi-issue closed
        negotiation. The competition was based on the GEnius environment,
        which is a General Environment for Negotiation with Intelligent multi-purpose
        Usage Simulation. The first competition was held in conjunction with
        the Ninth International Conference on Autonomous Agents and Multiagent
        Systems (AAMAS-10) and was comprised of seven teams. This paper presents
        an overview of the competition, as well as general and contrasting
        approaches towards negotiation strategies that were adopted by the
        participants of the competition. Based on analysis in post--tournament
        experiments, the paper also attempts to provide some insights with
        regard to effective approaches towards the design of negotiation
        strategies.},
  isbn = {978-3-642-24695-1},
  owner = {tim}
}

@INPROCEEDINGS{Baarslag10ANACshorter,
  author = {Baarslag, Tim and Hindriks, Koen V. and Jonker, Catholijn M. and Kraus,
        Sarit and Lin, Raz},
  title = {The First Automated Negotiating Agents Competition ({ANAC} 2010)},
  booktitle = {New Trends in Agent-based Complex Automated Negotiations},
  year = {2012},
  abstract = {Motivated by the challenges of bilateral negotiations between people
        and automated agents we organized the first automated negotiating
        agents competition (ANAC 2010). The purpose of the competition is
        to facilitate the research in the area bilateral multi-issue closed
        negotiation. The competition was based on the GEnius environment,
        which is a General Environment for Negotiation with Intelligent multi-purpose
        Usage Simulation. The first competition was held in conjunction with
        the Ninth International Conference on Autonomous Agents and Multiagent
        Systems (AAMAS-10) and was comprised of seven teams. This paper presents
        an overview of the competition, as well as general and contrasting
        approaches towards negotiation strategies that were adopted by the
        participants of the competition. Based on analysis in post--tournament
        experiments, the paper also attempts to provide some insights with
        regard to effective approaches towards the design of negotiation
        strategies.},
  isbn = {978-3-642-24695-1},
  owner = {tim},
  timestamp = {2013.04.20}
}

@InProceedings{Baarslag13AAMAS,
  author    = {Baarslag, Tim and Hindriks, Koen V.},
  title     = {Accepting Optimally in Automated Negotiation with Incomplete Information},
  booktitle = {Proceedings of the 2013 International Conference on Autonomous Agents and Multi-agent Systems},
  year      = {2013},
  series    = {AAMAS '13},
  pages     = {715--722},
  address   = {Richland, SC},
  publisher = {International Foundation for Autonomous Agents and Multiagent Systems},
  abstract  = {When a negotiating agent is presented with an offer by its opponent,
        it is faced with a decision: it can accept the offer that is currently
        on the table, or it can reject it and continue the negotiation. Both
        options involve an inherent risk: continuing the negotiation carries
        the risk of forgoing a possibly optimal offer, whereas accepting
        runs the risk of missing out on an even better future offer. We approach
        the decision of whether to accept as a sequential decision problem,
        by modeling the bids received as a stochastic process. We argue that
        this is a natural choice in the context of a negotiation with incomplete
        information, where the future behavior of the opponent is uncertain.
        We determine the optimal acceptance policies for particular opponent
        classes and we present an approach to estimate the expected range
        of offers when the type of opponent is unknown. We apply our method
        against a wide range of opponents, and compare its performance with
        acceptance mechanisms of state-of-the-art negotiation strategies.
        The experiments show that the proposed approach is able to find the
        optimal time to accept, and improves upon widely used existing acceptance
        mechanisms.},
  acmid     = {2485033},
  isbn      = {978-1-4503-1993-5},
  keywords  = {acceptance strategy, negotiation, optimal stopping},
  location  = {Saint Paul, Minnesota, USA},
  numpages  = {8},
  pdf       = {pub/Accepting_Optimally_in_Automated_Negotiation_with_Incomplete_Information.pdf},
  url       = {http://dl.acm.org/citation.cfm?id=2484920.2485033},
}

@InProceedings{BaarslagOptimalBiddingACAN,
  author    = {Tim Baarslag and Rafik Hadfi and Koen V. Hindriks and Takayuki Ito and Catholijn M. Jonker},
  title     = {Optimal Non-adaptive Concession Strategies with Incomplete Information},
  booktitle = {Recent Advances in Agent-based Complex Automated Negotiation},
  year      = {2016},
  editor    = {Fukuta, Naoki and Ito, Takayuki and Zhang, Minjie and Fujita, Katsuhide and Robu, Valentin},
  volume    = {638},
  pages     = {39--54},
  address   = {Cham},
  publisher = {Springer International Publishing},
  abstract  = {When two parties conduct a negotiation, they must be willing to make concessions to achieve a mutually acceptable deal, or face the consequences of no agreement. Therefore, negotiators normally make larger concessions as the deadline is closing in. Many time-based concession strategies have already been proposed, but they are typically heuristic in nature, and therefore, it is still unclear what is the right way to concede toward the opponent. Our aim is to construct optimal concession strategies against specific classes of acceptance strategies. We apply sequential decision techniques to find analytical solutions that optimize the expected utility of the bidder, given certain strategy sets of the opponent. Our solutions turn out to significantly outperform current state of the art approaches in terms of obtained utility. Our results open the way for a new and general concession strategy that can be combined with various existing learning and accepting techniques to yield a fully-fledged negotiation strategy for the alternating offers setting.},
  doi       = {10.1007/978-3-319-30307-9_3},
  isbn      = {978-3-319-30307-9},
  pdf       = {pub/Optimal_Non-adaptive_Concession_Strategies_with_Incomplete_Information.pdf},
  url       = {http://dx.doi.org/10.1007/978-3-319-30307-9_3},
}

@incollection{CUHKAgent,
year={2014},
isbn={978-4-431-54757-0},
booktitle={Novel Insights in Agent-based Complex Automated Negotiation},
volume={535},
series={Studies in Computational Intelligence},
editor={Marsa-Maestre, Ivan and Lopez-Carmona, Miguel A. and Ito, Takayuki and Zhang, Minjie and Bai, Quan and Fujita, Katsuhide},
doi={10.1007/978-4-431-54758-7_11},
title={CUHKAgent: An Adaptive Negotiation Strategy for Bilateral Negotiations over Multiple Items},
publisher={Springer Japan},
keywords={Adaption; Negotiation; Reinforcement learning},
author={Hao, Jianye and Leung, {Ho-fung}},
pages={171-179}
}

@ARTICLE{Her10,
  author = {Abdi, Herv\'{e} and Williams, Lynne J.},
  title = {Principal component analysis},
  journal = {Wiley Interdisciplinary Reviews: Computational Statistics},
  year = {2010},
  volume = {2},
  pages = {433--459},
  number = {4},
  doi = {10.1002/wics.101},
  issn = {1939-0068},
  keywords = {singular and eigen value decomposition, bilinear decomposition, factor
        scores and loadings, RESS PRESS, multiple factor analysis},
  publisher = {John Wiley \& Sons, Inc.},
  url = {http://dx.doi.org/10.1002/wics.101}
}

@MASTERSTHESIS{Afi13,
  author = {Afiouni, Einar Nour and Ovrelid, Leif Julian},
  title = {Negotiation for Strategic Video Games},
  school = {Norwegian University of Science and Technology, Department of Computer and Information Science},
  year = {2013},
  institution = {Norwegian University of Science and Technology, Department of Computer and Information Science},
  pages = {140},
  publisher = {Institutt for datateknikk og informasjonsvitenskap}
}

@ARTICLE{Agr09,
  author = {Agrawal, Manish K. and Chari, Kaushal},
  title = {Learning Negotiation Support Systems in Competitive Negotiations:
        A Study of Negotiation Behaviours and System Impacts},
  journal = {International Journal of Intelligent Information Technologies},
  year = {2009},
  volume = {5},
  pages = {1--23},
  number = {1},
  owner = {Mark},
  timestamp = {2013.05.28}
}



@PHDTHESIS{An11,
  author = {An, B.},
  title = {Automated negotiation for complex multi-agent resource allocation},
  school = {University of Massachusetts Amherst},
  year = {2011},
  owner = {Mark},
  timestamp = {2013.01.25}
}

@article{An11strategic,
 author = {An, Bo and Lesser, Victor R. and Sim, Kwang Mong},
 title = {Strategic Agents for Multi-resource Negotiation},
 journal = {Autonomous Agents and Multi-Agent Systems},
 issue_date = {July 2011},
 volume = {23},
 number = {1},
 month = {Jul},
 year = {2011},
 issn = {1387-2532},
 pages = {114--153},
 numpages = {40},
 url = {http://dx.doi.org/10.1007/s10458-010-9137-2},
 doi = {10.1007/s10458-010-9137-2},
 acmid = {1969596},
 publisher = {Kluwer Academic Publishers},
 address = {Hingham, MA, USA},
 keywords = {Automated negotiation, Multi-resource, Negotiation strategy},
} 

@ARTICLE{An12,
  author = {An, Bo and Gatti, Nicola and Lesser, Victor R.},
  title = {Bilateral bargaining with one-sided uncertain reserve prices},
  journal = {Autonomous Agents and Multi-Agent Systems},
  year = {2013},
  volume = {26},
  pages = {420-455},
  doi = {10.1007/s10458-012-9198-5},
  issn = {1387-2532},
  issue = {3},
  keywords = {Negotiation; Bargaining; Autonomous agents; Equilibrium},
  language = {English},
  owner = {Mark},
  publisher = {Springer US},
  timestamp = {2013.02.12},
  url = {http://dx.doi.org/10.1007/s10458-012-9198-5}
}

@INPROCEEDINGS{An09,
  author = {An, B. and Gatti, N. and Lesser, V.R.},
  title = {Bilateral bargaining with one-sided two-type uncertainty},
  booktitle = {Proceedings of the 2009 IEEE/WIC/ACM International Joint Conference on Web Intelligence and Intelligent Agent Technology},
  volume = {2},
  year = {2009},
  pages = {403--410},
  organization = {IEEE Computer Society},
  owner = {Mark},
  timestamp = {2013.02.06}
}

@INPROCEEDINGS{An09extending,
  author = {Bo An and Gatti, N. and Lesser, V.R.},
  title = {Extending Alternating-Offers Bargaining in One-to-Many and Many-to-Many Settings},
  booktitle = {Proceedings of the 2009 IEEE/WIC/ACM International Conference on
        Intelligent Agent Technology, IAT 2009, Milan, Italy},
  year = {2009},
  volume = {2},
  pages = {423-426},
  abstract = {Automating negotiations in markets where multiple buyers and sellers
        operate is a scientific challenge of extraordinary importance. One-to-one
        negotiations are classically studied as bilateral bargaining problems,
        while one-to-many and many-to-many negotiations are studied as auctioning
        problems. This paper aims at bridging together these two approaches,
        analyzing agents' strategic behavior in one-to-many and many-to-many
        negotiations when agents follow the alternating-offers bargaining
        protocol [5]. First, we propose a novel mechanism that captures the
        peculiarities of these settings. Then, we preliminarily explore how
        uncertainty over reserve prices and deadlines can affect equilibrium
        strategies. Surprisingly, the computation of the equilibrium for
        realistic ranges of the parameters in one-to-many settings is reduced
        to the computation of the equilibrium either in one-to-one settings
        with uncertainty or in one-to-many settings without uncertainty.},
  doi = {10.1109/WI-IAT.2009.188},
  keywords = {Computational complexity;Computer science;Conferences;Consumer electronics;Game
        theory;Intelligent agent;Protocols;USA Councils;Uncertainty}
}

@INPROCEEDINGS{ANAC2010AnExt,
author={An, Bo and Lesser, Victor R.},
  title = {Yushu: a Heuristic-Based Agent for Automated Negotiating Competition},
  booktitle = {New Trends in Agent-based Complex Automated Negotiations},
        volume={383},
        series={Studies in Computational Intelligence},
  year = {2012},
editor={Ito, Takayuki and Zhang, Minjie and Robu, Valentin and Fatima, Shaheen and Matsuo, Tokuro},
doi={10.1007/978-3-642-24696-8_9},
  pages = {145-149},
publisher={Springer Berlin Heidelberg},
  isbn = {978-3-642-24695-1},
  owner = {tim}
}

@ARTICLE{ANAC2010An,
  author = {Bo An and Victor R. Lesser},
  title = {Yushu: a Heuristic-Based Agent for Automated Negotiating Competition},
  journal = {This volume},
  year = {2012},
  pages = {145-149}
}

@ARTICLE{AnLes11,
  author = {An, Bo and Lesser, Victor R. and Sim, KwangMong},
  title = {Strategic agents for multi-resource negotiation},
  journal = {Autonomous Agents and Multi-Agent Systems},
  year = {2011},
  volume = {23},
  pages = {114-153},
  number = {1},
  doi = {10.1007/s10458-010-9137-2},
  issn = {1387-2532},
  keywords = {Automated negotiation; Negotiation strategy; Multi-resource},
  language = {English},
  publisher = {Springer US},
  url = {http://dx.doi.org/10.1007/s10458-010-9137-2}
}

@INCOLLECTION{An08,
  author = {An, Bo and Sim, Kwang Mong and Tang, Liang Gui and Miao, Chun Yan and Shen, Zhi Qi and Cheng, Dai Jie},
  title = {Negotiation Agents' Decision Making Using Markov Chains},
  booktitle = {Rational, Robust, and Secure Negotiations in Multi-Agent Systems},
  publisher = {Springer Berlin Heidelberg},
  year = {2008},
  editor = {Ito, Takayuki and Hattori, Hiromitsu and Zhang, Minjie and Matsuo, Tokuro},
  volume = {89},
  series = {Studies in Computational Intelligence},
  pages = {3-23},
  doi = {10.1007/978-3-540-76282-9_1},
  isbn = {978-3-540-76281-2},
  url = {http://dx.doi.org/10.1007/978-3-540-76282-9\_1}
}

@BOOK{Arr65,
  title = {The Theory of Risk Aversion},
  publisher = {Markham Publ. Co.},
  year = {1965},
  author = {Arrow, K.J.},
  journal = {Aspects of the Theory of Risk Bearing}
}

@INPROCEEDINGS{Ash03,
  author = {Ashri, R. and Rahwan, I. and Luck, M.},
  title = {Architectures for negotiating agents},
  booktitle = {Proceedings of the 3rd Central and Eastern European conference on
        Multi-agent systems},
  year = {2003},
  pages = {136--146},
  organization = {Springer-Verlag},
  owner = {Mark},
  timestamp = {2012.02.05}
}

@BOOK{Asi82,
  title = {Asimov's Biographical Encyclopedia of Science and Technology: The Lives and Achievements of 1195 Great Scientists from Ancient Times to the Present, Chronologically Arranged, Second Revised Edition},
  publisher = {Doubleday},
  year = {1982},
  author = {Asimov, I.},
  series = {Equinox book},
  isbn = {9780380006199},
  lccn = {78139003},
  url = {http://books.google.nl/books?id=ADjYAAAAMAAJ}
}

@BOOK{Axe84,
  title={The Evolution of Cooperation},
  author={Axelrod, Robert},
  year={1984},
  publisher={Basic Books},
    address = {New York, NY, USA}
}

@ARTICLE{Axe88,
  author = {Axelrod, Robert and Dion, Douglas},
  title = {The Further Evolution of Cooperation},
  journal = {Science},
  year = {1988},
  volume = {242},
  pages = {1385--1390},
  number = {4884},
  month = {Dec},
  abstract = {Axelrod's model of the evolution of cooperation was based on the iterated
        Prisoner's Dilemma. Empirical work following this approach has helped
        establish the prevalence of cooperation based on reciprocity. Theoretical
        work has led to a deeper understanding of the role of other factors
        in the evolution of cooperation: the number of players, the range
        of possible choices, variation in the payoff structure, noise, the
        shadow of the future, population dynamics, and population structure.
        10.1126/science.242.4884.1385},
  citeulike-article-id = {2462803},
  citeulike-linkout-0 = {http://dx.doi.org/10.1126/science.242.4884.1385},
  citeulike-linkout-1 = {http://www.sciencemag.org/cgi/content/abstract/242/4884/1385},
  citeulike-linkout-2 = {http://view.ncbi.nlm.nih.gov/pubmed/17802133},
  citeulike-linkout-3 = {http://www.hubmed.org/display.cgi?uids=17802133},
  day = {9},
  doi = {10.1126/science.242.4884.1385},
  keywords = {axelrod, cooperation, evolution, memetics},
  owner = {tim},
  posted-at = {2008-03-04 02:07:44},
  priority = {4},
  timestamp = {2010.03.03},
  url = {http://dx.doi.org/10.1126/science.242.4884.1385}
}

@Article{Ayd14,
  author     = {Aydo\u{g}an, Reyhan and Baarslag, Tim and Hindriks, Koen V. and Jonker, Catholijn M. and Yolum, P{\i}nar},
  title      = {Heuristics for Using CP-nets in Utility-based Negotiation Without Knowing Utilities},
  journal    = {Knowledge and Information Systems},
  year       = {2015},
  volume     = {45},
  number     = {2},
  pages      = {357--388},
  month      = nov,
  acmid      = {2830202},
  address    = {New York, NY, USA},
  doi        = {10.1007/s10115-014-0798-z},
  issn       = {0219-1377},
  issue_date = {November 2015},
  keywords   = {Automated negotiation, CP-nets, Heuristic-based approaches, Qualitative preferences},
  numpages   = {32},
  pdf        = {http://dx.doi.org/10.1007/s10115-014-0798-z},
  publisher  = {Springer-Verlag New York, Inc.},
  url        = {http://dx.doi.org/10.1007/s10115-014-0798-z},
  abstract       = {CP-nets have proven to be an effective representation for capturing preferences. However, their use in automated negotiation is not straightforward because, typically, preferences in CP-nets are partially ordered and negotiating agents are required to compare any two outcomes based on a request and an offer in order to negotiate effectively. If agents know how to generate total orders from their CP-nets, they can make this comparison. This paper proposes heuristics that enable the use of CP-nets in utility-based negotiations by generating total orderings. To validate this approach, the paper compares the performance of CP-nets with our heuristics with the performance of UCP-nets that are equipped with complete preference orderings. Our results show that we can achieve comparable performance in terms of the outcome utility. More importantly, one of our proposed heuristics can achieve this performance with significantly smaller number of interactions compared to UCP-nets.}
}

@InProceedings{Ayd11,
  author      = {Reyhan Aydo{\u{g}}an and Tim Baarslag and Koen V. Hindriks and Catholijn M. Jonker and P{\i}nar Yolum},
  title       = {Heuristic-based Approaches for {CP}-Nets in Negotiation},
  booktitle   = {Complex Automated Negotiations: Theories, Models, and Software Competitions},
  year        = {2013},
  editor      = {Ito, Takayuki and Zhang, Minjie and Robu, Valentin and Matsuo, Tokuro},
  volume      = {435},
  series      = {Studies in Computational Intelligence},
  pages       = {113-123},
  publisher   = {Springer Berlin Heidelberg},
  abstract    = {CP-Nets have proven to be an effective representation for capturing
        preferences. However, their use in multiagent negotiation is not
        straightforward. The main reason for this is that CP-Nets capture
        partial ordering of preferences, whereas negotiating agents are required
        to compare any two outcomes based on the request and offers. This
        makes it necessary for agents to generate total orders from their
        CP-Nets. We have previously proposed a heuristic to generate total
        orders from a given CP-Net. This paper proposes another heuristic
        based on Borda count, applies it in negotiation, and compares its
        performance with the previous heuristic.},
  attachments = {http://ii.tudelft.nl/sites/default/files/ACAN2011CPNetHeuristics.pdf},
  doi         = {10.1007/978-3-642-30737-9\_7},
  isbn        = {978-3-642-30736-2},
  keyword     = {Engineering},
  pdf         = {pub/Heuristic-based_approaches_for_CP-nets_in_negotiation.pdf},
  url         = {http://dx.doi.org/10.1007/978-3-642-30737-9\_7},
}

@INCOLLECTION{Ayd12Preference,
  author = {Aydo{\u{g}}an, Reyhan and Yolum, P{\i}nar},
  title = {The Effect of Preference Representation on Learning Preferences in
        Negotiation},
  booktitle = {New Trends in Agent-Based Complex Automated Negotiations},
  publisher = {Springer Berlin Heidelberg},
  year = {2012},
  editor = {Ito, Takayuki and Zhang, Minjie and Robu, Valentin and Fatima, Shaheen
        and Matsuo, Tokuro},
  volume = {383},
  series = {Studies in Computational Intelligence},
  pages = {3-20},
  doi = {10.1007/978-3-642-24696-8\_1},
  isbn = {978-3-642-24695-1},
  language = {English},
  url = {http://dx.doi.org/10.1007/978-3-642-24696-8\_1}
}

@ARTICLE{Ayd12,
  author = {Aydo{\u{g}}an, Reyhan and Yolum, P{\i}nar},
  title = {Learning opponent's preferences for effective negotiation: an approach
        based on concept learning},
  journal = {Autonomous Agents and Multi-Agent Systems},
  year = {2012},
  volume = {24},
  pages = {104-140},
  abstract = {We consider automated negotiation as a process carried out by software
        agents to reach a consensus. To automate negotiation, we expect agents
        to understand their user's preferences, generate offers that will
        satisfy their user, and decide whether counter offers are satisfactory.
        For this purpose, a crucial aspect is the treatment of preferences.
        An agent not only needs to understand its own user's preferences,
        but also its opponent's preferences so that agreements can be reached.
        Accordingly, this paper proposes a learning algorithm that can be
        used by a producer during negotiation to understand consumer's needs
        and to offer services that respect consumer's preferences. Our proposed
        algorithm is based on inductive learning but also incorporates the
        idea of revision. Thus, as the negotiation proceeds, a producer can
        revise its idea of the consumer's preferences. The learning is enhanced
        with the use of ontologies so that similar service requests can be
        identified and treated similarly. Further, the algorithm is targeted
        to learning both conjunctive as well as disjunctive preferences.
        Hence, even if the consumer's preferences are specified in complex
        ways, our algorithm can learn and guide the producer to create well-targeted
        offers. Further, our algorithm can detect whether some preferences
        cannot be satisfied early and thus consensus cannot be reached. Our
        experimental results show that the producer using our learning algorithm
        negotiates faster and more successfully with customers compared to
        several other algorithms.},
  affiliation = {Department of Computer Engineering, Bogazici University, 34342 Bebek,
        Istanbul, Turkey},
  issn = {1387-2532},
  issue = {1},
  keyword = {Computer Science},
  publisher = {Springer Netherlands},
  url = {http://dx.doi.org/10.1007/s10458-010-9147-0}
}

@INPROCEEDINGS{Ayd07,
  author = {Aydo{\u{g}}an, Reyhan and Yolum, P{\i}nar},
  title = {Learning consumer preferences using semantic similarity},
  booktitle = {Proceedings of the 6th international joint conference on Autonomous
        agents and multiagent systems},
  year = {2007},
  pages = {229},
  organization = {ACM},
  owner = {Mark},
  timestamp = {2013.02.06}
}

@INPROCEEDINGS{Ayd02,
  author = {Reyhan Aydo{\u{g}}an and P{\i}nar Yolum},
  title = {Learning Consumer Preferences for Content-Oriented Negotiation},
  booktitle = {AAMAS Workshop on Business Agents and the Semantic Web (BASeWEB)},
  year = {2006},
  pages = {43--52},
  month = {May},
  publisher = {ACM Press},
  owner = {Mark},
  timestamp = {2013.06.15}
}

@InProceedings{BaarslagComponentAnalysis,
  author    = {Tim Baarslag and Alexander S.Y. Dirkzwager and Koen V. Hindriks and Catholijn M. Jonker},
  title     = {The Significance of Bidding, Accepting and Opponent Modeling in Automated Negotiation},
  booktitle = {21st European Conference on Artificial Intelligence},
  year      = {2014},
  volume    = {263},
  series    = {Frontiers in Artificial Intelligence and Applications},
  pages     = {27-32},
  abstract  = {Given the growing interest in automated negotiation, the search for effective strategies has produced a variety of different negotiation agents. Despite their diversity, there is a common structure to their design. A negotiation agent comprises three key components: the bidding strategy, the opponent model and the acceptance criteria. We show that this three-component view of a negotiating architecture not only provides a useful basis for developing such agents but also provides a useful analytical tool. By combining these components in varying ways, we are able to demonstrate the contribution of each component to the overall negotiation result, and thus determine the key contributing components. Moreover, we are able to study the interaction between components and present detailed interaction effects. Furthermore, we find that the bidding strategy in particular is of critical importance to the negotiator's success and far exceeds the importance of opponent preference modeling techniques. Our results contribute to the shaping of a research agenda for negotiating agent design by providing guidelines on how agent developers can spend their time most effectively.},
  location = {Prague},
  publisher = {IOS Press},
  doi       = {10.3233/978-1-61499-419-0-27},
  pdf       = {pub/The_significance_of_bidding_accepting_and_opponent_modeling_in_automated_negotiation.pdf},
  url       = {http://ebooks.iospress.nl/volumearticle/36911},
}

@InProceedings{Baarslag13AAMASDC,
  author    = {Tim Baarslag},
  title     = {Designing an Automated Negotiator: Learning What to Bid and when to Stop},
  booktitle = {Proceedings of the 2013 International Conference on Autonomous Agents and Multi-agent Systems},
  year      = {2013},
  series    = {AAMAS '13},
  pages     = {1419--1420},
  address   = {Richland, SC},
  publisher = {International Foundation for Autonomous Agents and Multiagent Systems},
  abstract  = {This paper describes the PhD research topic of the author on designing an automated negotiator. One of the key challenges of designing a successful negotiation agent is that usually only limited information is available about the other party. Therefore, we need to combine various learning techniques to decide what offers to make, and when to accept. The research goal is to investigate techniques for developing a versatile automated negotiator that can effectively conduct negotiations in an incomplete information setting.},
  acmid     = {2485255},
  isbn      = {978-1-4503-1993-5},
  keywords  = {artificial intelligence, machine learning, negotiation},
  location  = {St. Paul, MN, USA},
  numpages  = {2},
  pdf       = {pub/Designing_an_Automated_Negotiator-Learning_What_to_Bid_and_When_to_Stop.pdf},
  url       = {http://dl.acm.org/citation.cfm?id=2485255},
}

@INPROCEEDINGS{Baarslag13BNAIC,
  author = {Tim Baarslag},
  title = {Accepting Optimally in Automated Negotiation with Incomplete Information},
  booktitle = {Proceedings of the 25th Benelux Conference on Artificial Intelligence},
  year = {2013},
  abstract = {When a negotiating agent is presented with an offer by its opponent,
        it is faced with a decision: it can accept the offer that is currently
        on the table, or it can reject it and continue the negotiation. Both
        options involve an inherent risk: continuing the negotiation carries
        the risk of forgoing a possibly optimal offer, whereas accepting
        runs the risk of missing out on an even better future offer. We approach
        the decision of whether to accept as a sequential decision problem,
        by modeling the bids received as a stochastic process. We argue that
        this is a natural choice in the context of a negotiation with incomplete
        information, where the future behavior of the opponent is uncertain.
        We determine the optimal acceptance policies for particular opponent
        classes and we present an approach to estimate the expected range
        of offers when the type of opponent is unknown. We apply our method
        against a wide range of opponents, and compare its performance with
        acceptance mechanisms of state-of-the-art negotiation strategies.
        The experiments show that the proposed approach is able to find the
        optimal time to accept, and improves upon widely used existing acceptance
        mechanisms.},
  url = {http://repository.tudelft.nl/assets/uuid:12968c66-fa56-4a93-b933-708ddd78f7c5/paper_6.pdf}
}

@Article{Baarslag12ANAC2011,
  author     = {Tim Baarslag and Katsuhide Fujita and Enrico H. Gerding and Koen V. Hindriks and Takayuki Ito and Nicholas R. Jennings and Catholijn M. Jonker and Sarit Kraus and Raz Lin and Valentin Robu and Colin R. Williams},
  title      = {Evaluating practical negotiating agents: Results and analysis of the 2011 international competition},
  journal    = {Artificial Intelligence},
  year       = {2013},
  volume     = {198},
  pages      = {73 - 103},
  month      = {May},
  abstract   = {This paper presents an in-depth analysis and the key insights gained
        from the Second International Automated Negotiating Agents Competition
        (ANAC 2011). ANAC is an international competition that challenges
        researchers to develop successful automated negotiation agents for
        scenarios where there is no information about the strategies and
        preferences of the opponents. The key objectives of this competition
        are to advance the state-of-the-art in the area of practical bilateral
        multi-issue negotiations, and to encourage the design of agents that
        are able to operate effectively across a variety of scenarios. Eighteen
        teams from seven different institutes competed. This paper describes
        these agents, the setup of the tournament, including the negotiation
        scenarios used, and the results of both the qualifying and final
        rounds of the tournament. We then go on to analyse the different
        strategies and techniques employed by the participants using two
        methods: (i) we classify the agents with respect to their concession
        behaviour against a set of standard benchmark strategies and (ii)
        we employ empirical game theory (EGT) to investigate the robustness
        of the strategies. Our analysis of the competition results allows
        us to highlight several interesting insights for the broader automated
        negotiation community. In particular, we show that the most adaptive
        negotiation strategies, while robust across different opponents,
        are not necessarily the ones that win the competition. Furthermore,
        our EGT analysis highlights the importance of considering metrics,
        in addition to utility maximisation (such as the size of the basin
        of attraction), in determining what makes a successful and robust
        negotiation agent for practical settings.},
  acmid      = {2480280},
  address    = {Essex, UK},
  doi        = {10.1016/j.artint.2012.09.004},
  issn       = {0004-3702},
  issue_date = {May, 2013},
  numpages   = {31},
  pdf        = {pub/Evaluating_practical_negotiating_agents-results_and_analysis_of_the_2011_international_competition.pdf},
  publisher  = {Elsevier Science Publishers Ltd.},
  url        = {http://dx.doi.org/10.1016/j.artint.2012.09.004},
}

@ARTICLE{Baarslag12ANAC2011short,
  author = {Tim Baarslag and Katsuhide Fujita and Enrico H. Gerding and Koen V.
        Hindriks and Takayuki Ito and Nicholas R. Jennings and Catholijn M.
        Jonker and Sarit Kraus and Raz Lin and Valentin Robu and Colin R.
        Williams},
  title = {Evaluating Practical Negotiating Agents: Results and Analysis of     the 2011 International Competition},
  journal = {Artificial Intelligence},
  year = {2013},
  abstract = {This paper presents an in-depth analysis and the key insights gained
        from the Second International Automated Negotiating Agents Competition
        (ANAC 2011). ANAC is an international competition that challenges
        researchers to develop successful automated negotiation agents for
        scenarios where there is no information about the strategies and
        preferences of the opponents. The key objectives of this competition
        are to advance the state-of-the-art in the area of practical bilateral
        multi-issue negotiations, and to encourage the design of agents that
        are able to operate effectively across a variety of scenarios. Eighteen
        teams from seven different institutes competed. This paper describes
        these agents, the setup of the tournament, including the negotiation
        scenarios used, and the results of both the qualifying and final
        rounds of the tournament. We then go on to analyse the different
        strategies and techniques employed by the participants using two
        methods: (i) we classify the agents with respect to their concession
        behaviour against a set of standard benchmark strategies and (ii)
        we employ empirical game theory (EGT) to investigate the robustness
        of the strategies. Our analysis of the competition results allows
        us to highlight several interesting insights for the broader automated
        negotiation community. In particular, we show that the most adaptive
        negotiation strategies, while robust across different opponents,
        are not necessarily the ones that win the competition. Furthermore,
        our EGT analysis highlights the importance of considering metrics,
        in addition to utility maximisation (such as the size of the basin
        of attraction), in determining what makes a successful and robust
        negotiation agent for practical settings.},
  issn = {0004-3702},
  owner = {Mark},
  timestamp = {2013.04.20}
}

@InProceedings{Baarslag12AI,
  author    = {Tim Baarslag and Mark J.C. Hendrikx and Koen V. Hindriks and Catholijn M. Jonker},
  title     = {Measuring the Performance of Online Opponent Models in Automated Bilateral Negotiation},
  booktitle = {AI 2012: Advances in Artificial Intelligence},
  year      = {2012},
  editor    = {Michael Thielscher and Dongmo Zhang},
  volume    = {7691},
  series    = {Lecture Notes in Computer Science},
  pages     = {1--14},
  publisher = {Springer Berlin Heidelberg},
  abstract  = {An important aim in bilateral negotiations is to achieve a win-win solution for both parties; therefore, a critical aspect of a negotiating agent's success is its ability to take the opponent's preferences into account. Every year, new negotiation agents are introduced with better learning techniques to model the opponent. Our main goal in this work is to evaluate and compare the performance of a selection of state-of-the-art online opponent modeling techniques in negotiation, and to determine under which circumstances they are beneficial in a real-time, online negotiation setting. Towards this end, we provide an overview of the factors influencing the quality of a model and we analyze how the performance of opponent models depends on the negotiation setting. This results in better insight into the performance of opponent models, and allows us to pinpoint well-performing opponent modeling techniques that did not receive much previous attention in literature.},
  doi       = {10.1007/978-3-642-35101-3_1},
  isbn      = {978-3-642-35100-6},
  keywords  = {Negotiation; Opponent Model Performance; Quality Measures},
  location  = {Heidelberg},
  pdf       = {pub/Measuring_the_performance_of_online_opponent_models_in_automated_bilateral_negotiation.pdf},
  url       = {http://dx.doi.org/10.1007/978-3-642-35101-3_1},
}

@InProceedings{Baarslag13AITshort,
  author    = {Baarslag, Tim and Hendrikx, Mark J.C. and Hindriks, Koen V. and Jonker, Catholijn M.},
  title     = {Predicting the Performance of Opponent Models in Automated Negotiation},
  booktitle = {IEEE/WIC/ACM},
  year      = {2013},
  volume    = {2},
  month     = {Nov},
  doi       = {10.1109/WI-IAT.2013.91},
  keywords  = {Intelligent agents;Machine learning;Multiagent systems},
}

@InProceedings{Baarslag13AIT,
  author    = {Baarslag, Tim and Hendrikx, Mark J.C. and Hindriks, Koen V. and Jonker, Catholijn M.},
  title     = {Predicting the Performance of Opponent Models in Automated Negotiation},
  booktitle = {Proceedings of the 2013 IEEE/WIC/ACM International Joint Conferences on Web Intelligence (WI) and Intelligent Agent Technologies (IAT)},
  series = {WI-IAT '13},
  year      = {2013},
  volume    = {2},
  pages     = {59-66},
  numpages  = {8},
  month     = {Nov},
  abstract  = {When two agents settle a mutual concern by negotiating with each other,they usually do not share their preferences so as to avoid exploitation. In such a setting, the agents may need to analyze each other's behavior to make an estimation of the opponent's preferences. This process of opponent modeling makes it possible to find a satisfying negotiation outcome for both parties. A large number of such opponent modeling techniques have already been introduced, together with different measures to assess their quality. The quality of an opponent model can be measured in two different ways: one is to use the agent's performance as a benchmark for the model's quality, the other is to directly evaluate its accuracy by using similarity measures. Both methods have been used extensively, and both have their distinct advantages and drawbacks. In this work we investigate the exact relation between the two, and we pinpoint the measures for accuracy that best predict performance gain. This leads us to new insights in how to construct an opponent model, and what we need to measure when optimizing performance.},
  doi       = {10.1109/WI-IAT.2013.91},
  url = {http://dx.doi.org/10.1109/WI-IAT.2013.91},
  isbn = {978-0-7695-5145-6},
  acmid = {2569293},
  publisher = {IEEE Computer Society},
  address = {Washington, DC, USA},
  keywords = {Intelligent agents, Multiagent systems, Machine learning},
  pdf       = {pub/Predicting_the_performance_of_opponent_models_in_automated_negotiation.pdf},
}

@InCollection{BaarslagBOA,
  author    = {Tim Baarslag and Koen V. Hindriks and Mark J.C. Hendrikx and Alex S.Y. Dirkzwager and Catholijn M. Jonker},
  title     = {Decoupling Negotiating Agents to Explore the Space of Negotiation Strategies},
  booktitle = {Novel Insights in Agent-based Complex Automated Negotiation},
  publisher = {Springer, Japan},
  year      = {2014},
  editor    = {Marsa-Maestre, Ivan and Lopez-Carmona, Miguel A. and Ito, Takayuki and Zhang, Minjie and Bai, Quan and Fujita, Katsuhide},
  volume    = {535},
  series    = {Studies in Computational Intelligence},
  pages     = {61-83},
  abstract  = {Every year, automated negotiation agents are improving on various
        domains. However, given a set of automated negotiation agents, current
        methods allow to determine which strategy is best in terms of utility,
        but not so much the reason of success. In order to study the performance
        of the individual components of a negotiation strategy, we introduce
        an architecture that distinguishes three components which together
        constitute a negotiation strategy: the bidding strategy, the opponent
        model, and the acceptance strategy. Our contribution to the field
        of bilateral negotiation is twofold: first, we show that existing
        state-of-the-art agents are compatible with this architecture by
        re-implementing them in the new framework; secondly, as an application
        of our architecture, we systematically explore the space of possible
        strategies by recombining different strategy components, resulting
        in negotiation strategies that improve upon the current state-of-the-art
        in automated negotiation.},
  doi       = {10.1007/978-4-431-54758-7\_4},
  isbn      = {978-4-431-54757-0},
  keywords  = {Acceptance condition; Automated bilateral negotiation; Bidding strategy; BOA architecture; Component-based; Opponent model},
  pdf       = {pub/Decoupling_Negotiating_Agents_to_Explore_the_Space_of_Negotiation_Strategies.pdf},
  url       = {http://dx.doi.org/10.1007/978-4-431-54758-7\_4},
}

@INPROCEEDINGS{Baarslag12ACANshort,
  author = {Tim Baarslag and Koen V. Hindriks and Mark J.C. Hendrikx and Alex S.Y. Dirkzwager
        and Catholijn M. Jonker},
  title = {Decoupling Negotiating Agents to Explore the Space of Negotiation
        Strategies},
  booktitle = {Proceedings of The Fifth International Workshop on Agent-based Complex
        Automated Negotiations (ACAN 2012)},
  year = {2012},
  abstract = {Every year, automated negotiation agents are improving on various
        domains. However, given a set of automated negotiation agents, current
        methods allow to determine which strategy is best in terms of utility,
        but not so much the reason of success. In order to study the performance
        of the individual components of a negotiation strategy, we introduce
        an architecture that distinguishes three components which together
        constitute a negotiation strategy: the bidding strategy, the opponent
        model, and the acceptance strategy. Our contribution to the field
        of bilateral negotiation is twofold: first, we show that existing
        state-of-the-art agents are compatible with this architecture by
        re-implementing them in the new framework; secondly, as an application
        of our architecture, we systematically explore the space of possible
        strategies by recombining different strategy components, resulting
        in negotiation strategies that improve upon the current state-of-the-art
        in automated negotiation.}
}

@INPROCEEDINGS{Baarslag12BNAIC,
  author = {Tim Baarslag and Koen V. Hindriks and Mark J.C. Hendrikx and Alex S.Y. Dirkzwager and Catholijn M. Jonker},
  title = {Decoupling Negotiating Agents to Explore the Space of Negotiation Strategies},
  booktitle = {Proceedings of the 24th Benelux Conference on Artificial Intelligence},
  year = {2012},
  abstract = {Every year, automated negotiation agents are improving on various
        domains. However, given a set of automated negotiation agents, current
        methods allow to determine which strategy is best in terms of utility,
        but not so much the reason of success. In order to study the performance
        of the individual components of a negotiation strategy, we introduce
        an architecture that distinguishes three components which together
        constitute a negotiation strategy: the bidding strategy, the opponent
        model, and the acceptance strategy. Our contribution to the field
        of bilateral negotiation is twofold: first, we show that existing
        state-of-the-art agents are compatible with this architecture by
        re-implementing them in the new framework; secondly, as an application
        of our architecture, we systematically explore the space of possible
        strategies by recombining different strategy components, resulting
        in negotiation strategies that improve upon the current state-of-the-art
        in automated negotiation.},
  issn = {1568-7805},
  url = {http://ii.tudelft.nl/?q=node/7808}
}

@INPROCEEDINGS{Baarslag13OM,
  author = {Baarslag, Tim and Hendrikx, Mark J.C. and Hindriks, Koen V. and Jonker, Catholijn M.},
  title = {Predicting the Performance of Opponent Models in Automated Negotiation},
  booktitle = {International Joint Conferences on Web Intelligence (WI) and Intelligent Agent Technologies (IAT), 2013 IEEE/WIC/ACM},
  year = {2013},
  volume = {2},
  pages = {59-66},
  abstract = {When two agents settle a mutual concern by negotiating with each other,
        they usually do not share their preferences so as to avoid exploitation.
        In such a setting, the agents may need to analyze each other's behavior
        to make an estimation of the opponent's preferences. This process
        of opponent modeling makes it possible to find a satisfying negotiation
        outcome for both parties. A large number of such opponent modeling
        techniques have already been introduced, together with different
        measures to assess their quality. The quality of an opponent model
        can be measured in two different ways: one is to use the agent's
        performance as a benchmark for the model's quality, the other is
        to directly evaluate its accuracy by using similarity measures. Both
        methods have been used extensively, and both have their distinct
        advantages and drawbacks. In this work we investigate the exact relation
        between the two, and we pinpoint the measures for accuracy that best
        predict performance gain. This leads us to new insights in how to
        construct an opponent model, and what we need to measure when optimizing
        performance.},
  doi = {10.1109/WI-IAT.2013.91},
  url = {http://dx.doi.org/10.1109/WI-IAT.2013.91},
  keywords = {Intelligent agents;Machine learning;Multiagent systems}
}

@InProceedings{Baarslag12ACAN,
  author    = {Tim Baarslag and Koen V. Hindriks and Mark J.C. Hendrikx and Alex S.Y. Dirkzwager and Catholijn M. Jonker},
  title     = {Decoupling Negotiating Agents to Explore the Space of Negotiation Strategies},
  booktitle = {Proceedings of The Fifth International Workshop on Agent-based Complex Automated Negotiations (ACAN 2012)},
  year      = {2012},
  abstract  = {Every year, automated negotiation agents are improving on various
        domains. However, given a set of automated negotiation agents, current
        methods allow to determine which strategy is best in terms of utility,
        but not so much the reason of success. In order to study the performance
        of the individual components of a negotiation strategy, we introduce
        an architecture that distinguishes three components which together
        constitute a negotiation strategy: the bidding strategy, the opponent
        model, and the acceptance strategy. Our contribution to the field
        of bilateral negotiation is twofold: first, we show that existing
        state-of-the-art agents are compatible with this architecture by
        re-implementing them in the new framework; secondly, as an application
        of our architecture, we systematically explore the space of possible
        strategies by recombining different strategy components, resulting
        in negotiation strategies that improve upon the current state-of-the-art
        in automated negotiation.},
  pdf       = {pub/Decoupling_Negotiating_Agents_to_Explore_the_Space_of_Negotiation_Strategies_ACAN_2012.pdf},
  url       = {http://ii.tudelft.nl/sites/default/files/boa.pdf},
}

@INPROCEEDINGS{Baarslag11BNAIC,
  author = {Tim Baarslag and Koen V. Hindriks and Catholijn M. Jonker},
  title = {Acceptance Conditions in Automated Negotiation},
  booktitle = {Proceedings of the 23rd Benelux Conference on Artificial Intelligence},
  year = {2011},
  editor = {Patrick De Causmaecker and Joris Maervoet and Tommy Messelis and Katja Verbeeck and Tim Vermeulen},
  pages = {363-365},
  attachments = {http://ii.tudelft.nl/sites/default/files/acceptance-mechanisms-extended-abstract.pdf},
  journal = {BNAIC 2011},
  url = {http://allserv.kahosl.be/bnaic2011/sites/default/files/bnaic2011\_submission\_47.pdf}
}

@InCollection{ANAC2011Baa,
  author    = {Baarslag, Tim and Hindriks, Koen V. and Jonker, Catholijn M.},
  title     = {A Tit for Tat Negotiation Strategy for Real-Time Bilateral Negotiations},
  booktitle = {Complex Automated Negotiations: Theories, Models, and Software Competitions},
  publisher = {Springer Berlin Heidelberg},
  year      = {2013},
  editor    = {Ito, Takayuki and Zhang, Minjie and Robu, Valentin and Matsuo, Tokuro},
  volume    = {435},
  series    = {Studies in Computational Intelligence},
  pages     = {229-233},
  abstract  = {We describe the strategy of our negotiating agent, Nice Tit for Tat Agent, which reached the finals of the 2011 Automated Negotiating Agent Competition. It uses a Tit for Tat strategy to select its offers in a negotiation, i.e.: initially it cooperates with its opponent, and in the following rounds of negotiation, it responds in kind to the opponent's actions.We give an overview of how to implement such a Tit for Tat strategy and discuss its merits in the setting of closed bilateral negotiation.},
  doi       = {10.1007/978-3-642-30737-9\_18},
  isbn      = {978-3-642-30736-2},
  pdf       = {pub/A_tit_for_tat_negotiation_strategy_for_real-time_bilateral_negotiations.pdf},
  url       = {http://dx.doi.org/10.1007/978-3-642-30737-9\_18},
}

@InProceedings{Baarslag11ACAN,
  author      = {Tim Baarslag and Koen V. Hindriks and Catholijn M. Jonker},
  title       = {Acceptance Conditions in Automated Negotiation},
  booktitle   = {Complex Automated Negotiations: Theories, Models, and Software Competitions},
  year        = {2013},
  editor      = {Ito, Takayuki and Zhang, Minjie and Robu, Valentin and Matsuo, Tokuro},
  volume      = {435},
  series      = {Studies in Computational Intelligence},
  pages       = {95-111},
  publisher   = {Springer Berlin Heidelberg},
  abstract    = {In every negotiation with a deadline, one of the negotiating parties
        has to accept an offer to avoid a break off. A break off is usually
        an undesirable outcome for both parties, therefore it is important
        that a negotiator employs a proficient mechanism to decide under
        which conditions to accept. When designing such conditions one is
        faced with the acceptance dilemma: accepting the current offer may
        be suboptimal, as better offers may still be presented. On the other
        hand, accepting too late may prevent an agreement from being reached,
        resulting in a break off with no gain for either party. Motivated
        by the challenges of bilateral negotiations between automated agents
        and by the results and insights of the automated negotiating agents
        competition (ANAC), we classify and compare state-of-the-art generic
        acceptance conditions. We focus on decoupled acceptance conditions,
        i.e. conditions that do not depend on the bidding strategy that is
        used. We performed extensive experiments to compare the performance
        of acceptance conditions in combination with a broad range of bidding
        strategies and negotiation domains. Furthermore we propose new acceptance
        conditions and we demonstrate that they outperform the other conditions
        that we study. In particular, it is shown that they outperform the
        standard acceptance condition of comparing the current offer with
        the offer the agent is ready to send out. We also provide insight
        in to why some conditions work better than others and investigate
        correlations between the properties of the negotiation environment
        and the efficacy of acceptance conditions.},
  attachments = {http://ii.tudelft.nl/sites/default/files/acceptance-mechanisms.pdf},
  doi         = {10.1007/978-3-642-30737-9\_6},
  isbn        = {978-3-642-30736-2},
  keyword     = {Engineering},
  pdf         = {pub/Acceptance_conditions_in_automated_negotiation.pdf},
  url         = {http://dx.doi.org/10.1007/978-3-642-30737-9\_6},
}

@InProceedings{Baarslag11PRIMA,
  author    = {Baarslag, Tim and Hindriks, Koen V. and Jonker, Catholijn M.},
  title     = {Towards a Quantitative Concession-Based Classification Method of Negotiation Strategies},
  booktitle = {Agents in Principle, Agents in Practice},
  year      = {2011},
  editor    = {Kinny, David and Hsu, Jane Yung-jen and Governatori, Guido and Ghose, Aditya K.},
  volume    = {7047},
  series    = {Lecture Notes in Computer Science},
  pages     = {143--158},
  address   = {Berlin, Heidelberg},
  publisher = {Springer Berlin Heidelberg},
  abstract  = {In order to successfully reach an agreement in a negotiation, both
        parties rely on each other to make concessions. The willingness to
        concede also depends in large part on the opponent. A concession
        by the opponent may be reciprocated, but the negotiation process
        may also be frustrated if the opponent does not concede at all. This
        process of concession making is a central theme in many of the classic
        and current automated negotiation strategies. In this paper, we present
        a quantitative classification method of negotiation strategies that
        measures the willingness of an agent to concede against different
        types of opponents. The method is then applied to classify some well-known
        negotiating strategies, including the agents of ANAC 2010. It is
        shown that the technique makes it easy to identify the main characteristics
        of negotiation agents, and can be used to group negotiation strategies
        into categories with common negotiation characteristics. We also
        observe, among other things, that different kinds of opponents call
        for a different approach in making concessions.},
  doi       = {http://dx.doi.org/10.1007/978-3-642-25044-6\_13},
  isbn      = {978-3-642-25043-9},
  keywords  = {automated bilateral negotiation, classification, competition, concession, cooperation, negotiation strategy},
  location  = {Wollongong, Australia},
  numpages  = {16},
  owner     = {tim},
  pdf       = {pub/Towards_a_quantitative_concession-based_classification_method_of_negotiation_strategies.pdf},
  url       = {http://dx.doi.org/10.1007/978-3-642-25044-6_13},
}

@INPROCEEDINGS{Bar02,
  author = {Bartolini, Claudio and Preist, Chris and Jennings, Nicholas R.},
  title = {A generic software framework for automated negotiation},
  booktitle = {First International Conference on Autonomous Agent and Multi-Agent
        Systems},
  year = {2002},
  owner = {Mark},
  timestamp = {2012.02.05}
}

@BOOK{Bat88,
  title = {Nonlinear regression analysis and its applications},
  publisher = {New York. John Wiley and Sons},
  year = {1988},
  author = {Bates, Douglas M. and Watts, Donald G.},
  journal = {Wiley series in probability and mathematical statistics. Applied
        probability and statistics},
  owner = {---},
  timestamp = {2011.07.10}
}

@INCOLLECTION{Baz92,
  author = {Max H. Bazerman and Margaret A. Neale},
  title = {Negotiator Rationality and Negotiator Cognition: The InteractiveRoles
        of Prescriptive and Descriptive Research},
  booktitle = {Negotiation Analysis},
  publisher = {The University of Michigan Press},
  year = {1992},
  editor = {H.P. Young},
  pages = {109-130}
}

@ARTICLE{beam97,
  author = {Beam, Carrie and Segev, Arie},
  title = {Automated negotiations: A survey of the state of the art},
  journal = {Wirtschaftsinformatik},
  year = {1997},
  volume = {39},
  pages = {263--268},
  number = {3},
  owner = {---},
  publisher = {Citeseer},
  timestamp = {2011.06.14}
}

@INPROCEEDINGS{Beh09Predict,
  author = {Beheshti, R. and Mozayani, N.},
  title = {Predicting Opponents Offers in Multi-agent Negotiations Using ARTMAP
        Neural Network},
  booktitle = {Proceedings of the 2009 Second International Conference on Future
        Information Technology and Management Engineering},
  year = {2009},
  series = {FITME '09},
  pages = {600--603},
  address = {Washington, DC, USA},
  publisher = {IEEE Computer Society},
  acmid = {1725263},
  isbn = {978-0-7695-3880-8},
  numpages = {4},
  owner = {Mark},
  timestamp = {2013.02.08}
}

@INPROCEEDINGS{Beh09Genetic,
  author = {Beheshti, R. and Rahmani, A.T.},
  title = {A Multi-objective Genetic Algorithm Method to Support Multi-agent
        Negotiations},
  booktitle = {Proceedings of the 2009 Second International Conference on Future
        Information Technology and Management Engineering},
  year = {2009},
  series = {FITME '09},
  pages = {596--599},
  acmid = {1725262},
  isbn = {978-0-7695-3880-8},
  numpages = {4},
  owner = {Mark},
  timestamp = {2013.02.08}
}

@ARTICLE{bei03,
  author = {Beil, D.R. and Wein, L.M.},
  title = {An inverse-optimization-based auction mechanism to support a multiattribute
        RFQ process},
  journal = {Management Science},
  year = {2003},
  volume = {49},
  pages = {1529-1545}
}

@INCOLLECTION{ANAC2011Ada,
  author = {Ben Adar, Mai and Sofy, Nadav and Elimelech, Avshalom},
  title = {Gahboninho: Strategy for Balancing Pressure and Compromise in Automated
        Negotiation},
  booktitle = {Complex Automated Negotiations: Theories, Models, and Software Competitions},
  publisher = {Springer Berlin Heidelberg},
  year = {2013},
  editor = {Ito, Takayuki and Zhang, Minjie and Robu, Valentin and Matsuo, Tokuro},
  volume = {435},
  series = {Studies in Computational Intelligence},
  pages = {205-208},
  doi = {10.1007/978-3-642-30737-9\_13},
  isbn = {978-3-642-30736-2},
  url = {http://dx.doi.org/10.1007/978-3-642-30737-9\_13}
}

@INCOLLECTION{ANAC2011Adashort,
  author = {Ben Adar, Mai and Sofy, Nadav and Elimelech, Avshalom},
  title = {Gahboninho: Strategy for Balancing Pressure and Compromise in Automated
        Negotiation},
  booktitle = {Complex Automated Negotiations: Theories, Models, and Software Competitions},
  publisher = {Springer Berlin Heidelberg},
  year = {2013},
  pages = {205-208},
  doi = {10.1007/978-3-642-30737-9\_13},
  isbn = {978-3-642-30736-2},
  url = {http://dx.doi.org/10.1007/978-3-642-30737-9\_13}
}

@MISC{Bic01,
  author = {Bichler, M. and Lee, J. and Lee, H.S. and Chung, J.},
  title = {ABSolute: An intelligent decision making framework for e-sourcing},
  year = {2001},
  pages = {195-201}
}

@ARTICLE{Bin89,
  author = {Binmore, Ken and Osborne, Martin J and Rubinstein, Ariel},
  title = {Noncooperative models of bargaining},
  journal = {Handbook of Game Theory with Economic Applications},
  year = {1992},
  volume = {1},
  pages = {179--225},
  owner = {Mark},
  publisher = {Elsevier},
  timestamp = {2013.02.12}
}

@BOOK{Bin07,
title = {Does Game Theory Work? The Bargaining Challenge},
author = {Binmore, Ken},
year = {2007},
volume = {1},
edition = {1},
publisher = {The MIT Press},
abstract = {This volume brings together all of Ken Binmore's influential experimental papers on bargaining along with newly written commentary in which Binmore discusses the underlying game theory and addresses the criticism leveled at it by behavioral economists. When Binmore began his experimental work in the 1980s, conventional wisdom held that game theory would not work in the laboratory, but Binmore and other pioneers established that game theory can often predict the behavior of experienced players very well in favorable laboratory settings. The case of human bargaining behavior is particularly challenging for game theory. Everyone agrees that human behavior in real-life bargaining situations is governed at least partly by considerations of fairness, but what happens in a laboratory when such fairness considerations supposedly conflict with game-theoretic predictions? Behavioral economists, who emphasize the importance of other-regarding or social preferences, sometimes argue that their findings threaten traditional game theory. Binmore disputes both their interpretations of their findings and their claims about what game theorists think it reasonable to predict. Binmore's findings from two decades of game theory experiments have made a lasting contribution to economics. These papers--some coauthored with other leading economists, including Larry Samuelson, Avner Shaked, and John Sutton--show that game theory does indeed work in favorable laboratory environments, even in the challenging case of bargaining.},
keywords = {game theory; bargaining; laboratory experimentation},
url = {http://EconPapers.repec.org/RePEc:mtp:titles:0262026074}
}



@ARTICLE{Bin99,
  author = {Binmore, Ken and Vulkan, Nir},
  title = {Applying game theory to automated negotiation},
  journal = {Netnomics},
  year = {1999},
  issn={1385-9587},
  volume = {1},
  pages = {1--9},
  number = {1},
  owner = {---},
publisher={Kluwer Academic Publishers},
  doi={10.1023/A:1011489402739},
  timestamp = {2011.05.29}
}

@ARTICLE{Bol00,
  author = {Terry L. Boles and Rachel T.A. Croson and J. Keith Murnighan},
  title = {Deception and Retribution in Repeated Ultimatum Bargaining},
  journal = {Organizational Behavior and Human Decision Processes},
  year = {2000},
  volume = {83},
  pages = {235 - 259},
  number = {2},
  abstract = {This paper investigates the dynamics of deception and retribution
        in repeated ultimatum bargaining. Anonymous dyads exchanged messages
        and offers in a series of four ultimatum bargaining games that had
        prospects for relatively large monetary outcomes. Variations in each
        party's knowledge of the other's resources and alternatives created
        opportunities for deception. Revelation of prior unknowns exposed
        deceptions and created opportunities for retribution in subsequent
        interactions. Results showed that although proposers and responders
        chose deceptive strategies almost equally, proposers told more outright
        lies. Both were more deceptive when their private information was
        never revealed, and proposers were most deceptive when their potential
        profits were largest. Revelation of proposers' lies had little effect
        on their subsequent behavior even though responders rejected their
        offers more than similar offers from truthful proposers or proposers
        whose prior deceit was never revealed. The discussion and conclusions
        address the dynamics of deception and retribution in repeated bargaining
        interactions.},
  doi = {http://dx.doi.org/10.1006/obhd.2000.2908},
  issn = {0749-5978},
  url = {http://www.sciencedirect.com/science/article/pii/S074959780092908X}
}

@ARTICLE{Bol91,
  author = {G. Bolton},
  title = {A comparative model of bargaining: Theory and evidence},
  journal = {American Economic Review},
  year = {1989},
  volume = {81},
  pages = {1096-1136},
  number = {5}
}

@INPROCEEDINGS{Bos04,
  author = {Bosse, Tibor and Jonker, Catholijn M. and Treur, Jan},
  title = {Experiments in human multi-issue negotiation: Analysis and support},
  booktitle = {Proceedings of the Third International Joint Conference on Autonomous
        Agents and Multiagent Systems},
  year = {2004},
  volume = {2},
  pages = {671--678},
  organization = {IEEE Computer Society},
  owner = {---},
  timestamp = {2011.05.22}
}

@INPROCEEDINGS{Bos05,
  author = {Bosse, Tibor and Jonker, Catholijn M.},
  title = {Human vs. Computer Behaviour in Multi-Issue Negotiation},
  booktitle = {Proceedings of the Rational, Robust, and Secure Negotiation Mechanisms
        in Multi-Agent Systems},
  year = {2005},
  month={Jul}, 
  series = {RRS '05},
  pages = {11--24},
  address = {Washington, DC, USA},
  publisher = {IEEE Computer Society},
  acmid = {1115279},
  doi = {10.1109/RRS.2005.8},
  isbn = {0-7695-2480-X},
  url = {http://dx.doi.org/10.1109/RRS.2005.8}
}

@INCOLLECTION{Bos05System,
author={Bosse, Tibor and Jonker, Catholijn M. and van der Meij, Lourens and Robu, Valentin and Treur, Jan},
  title = {A System for Analysis of Multi-Issue Negotiation},
  booktitle = {Software Agent-Based Applications, Platforms and Development Kits},
  publisher = {Birkh\"{o}user Basel},
  year = {2005},
  editor = {Unland, Rainer and Calisti, Monique and Klusch, Matthias},
  series = {Whitestein Series in Software Agent Technologies},
  pages = {253-279},
  doi = {10.1007/3-7643-7348-2\_11},
  isbn = {978-3-7643-7347-4},
  owner = {Mark},
  timestamp = {2013.02.12},
  url = {http://dx.doi.org/10.1007/3-7643-7348-2\_11}
}

@ARTICLE{Bos08,
  author = {Bosse, Tibor and Jonker, Catholijn M. and van der Meij, Lourens and
        Treur, Jan},
  title = {Automated formal analysis of human multi-issue negotiation processes},
  journal = {Multiagent and Grid Systems},
  year = {2008},
  volume = {4},
  pages = {213--233},
  number = {2},
  month = {Apr},
  acmid = {1402622},
  address = {Amsterdam, The Netherlands, The Netherlands},
  issn = {1574-1702},
  keywords = {Multi-issue negotiation, formal analysis, human, tool},
  numpages = {21},
  publisher = {IOS Press},
  url = {http://dl.acm.org/citation.cfm?id=1402618.1402622}
}

@ARTICLE{Bou04,
 author = {Boutilier, Craig and Brafman, Ronen I. and Domshlak, Carmel and Hoos, Holger H. and Poole, David},
  title = {{CP}-nets: A tool for representing and reasoning with conditional ceteris
        paribus preference statements},
  journal = {Journal of Artificial Intelligence Research},
  year = {2004},
  month = {Feb},
  volume = {21},
  pages = {135--191},
   issn = {1076-9757},
    publisher = {AI Access Foundation},
 address = {USA},
  abstract = {In many domains it is desirable to assess the preferences of users
        in a qualitative rather than quantitative way. Useful representations
        of qualitative preference orderings form an important component of
        automated decision tools. We propose a graphical representation of
        preferences that reflects conditional dependence and independence
        of preference statements under a ceteris paribus (all else being
        equal) interpretation. Such a representation is often compact and
        arguably quite natural in many circumstances. We provide a formal
        semantics for this model, and describe how the structure of the network
        can be exploited in several inference tasks, such as determining
        whether one outcome dominates (is preferred to) another, ordering
        a set outcomes according to the preference relation, and constructing
        the best outcome subject to available evidence.},
  citeulike-article-id = {3920707},
  citeulike-linkout-0 = {http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.12.3759},
  keywords = {utility\_representation},
  owner = {tim},
  posted-at = {2009-01-21 18:31:02},
  priority = {3},
  timestamp = {2010.07.01},
  url = {http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.12.3759}
}

@ARTICLE{bra04,
  author = {Brafman, R.I. and Tennenholtz, M.},
  title = {Efficient learning equilibrium},
  journal = {Artificial Intelligence},
  year = {2004},
  volume = {159},
  pages = {27-48},
  number = {1}
}

@INPROCEEDINGS{Bra07,
  author = {Brandt, F. and Sandholm, T. and Shoham, Y.},
  title = {Spiteful bidding in sealed-bid auctions},
  booktitle = {Proc. of Twentieth International Joint Conference on Artificial Intelligence},
  year = {2007},
  pages = {1207-1214}
}

@INCOLLECTION{Bra06,
  author = {Braun, Peter and Brzostowski, Jakub and Kersten, Gregory E. and Kim,
        Jin Baek and Kowalczyk, Ryszard and Strecker, Stefan and Vahidov,
        Rustam M.},
  title = {e-Negotiation Systems and Software Agents: Methods, Models, and Applications},
  booktitle = {Intelligent Decision-making Support Systems},
  publisher = {Springer London},
  year = {2006},
  series = {Decision Engineering},
  pages = {271-300},
  doi = {10.1007/1-84628-231-4\_15},
  isbn = {978-1-84628-228-7},
  owner = {Mark},
  timestamp = {2013.06.01},
  url = {http://dx.doi.org/10.1007/1-84628-231-4\_15}
}

@ARTICLE{Bra97,
  author = {Brazier, Frances M.T. and Dunin-Keplicz, Barbara M. and Jennings, Nicholas R. and Treur,
        Jan},
  title = {Formal Specification of Multi-Agent Systems: a Real World Case},
  journal = {International Journal of Co-operative Information Systems, IJCIS},
  year = {1997},
  volume = {6(1)},
  pages = {67-94}
}

@ARTICLE{Bra08,
  author = {Darius Braziunas and Craig Boutilier},
  title = {Elicitation of Factored Utilities},
  journal = {AI Magazine},
  year = {2008},
  volume = {29},
  pages = {79-92},
  number = {4},
  bibsource = {DBLP, http://dblp.uni-trier.de},
  ee = {http://www.aaai.org/ojs/index.php/aimagazine/article/view/2203}
}

@ARTICLE{Bro10,
  author = {Broekens, Joost and Jonker, Catholijn M. and Meyer, John-Jules Ch.},
  title = {Affective Negotiation Support Systems},
  journal = {Journal of Ambient Intelligence and Smart Environments},
  year = {2010},
  volume = {2},
  pages = {121--144},
  number = {2},
  month = {Apr},
  acmid = {1804779},
  address = {Amsterdam, The Netherlands},
  issn = {1876-1364},
  issue_date = {April 2010},
  keywords = {Affect, affective computing, negotiation, negotiation support systems,
        review},
  numpages = {24},
  publisher = {IOS Press},
  url = {http://dl.acm.org/citation.cfm?id=1804772.1804779}
}

@INCOLLECTION{Brz05,
  author = {Brzostowski, Jakub and Kowalczyk, Ryszard},
  title = {Modelling partner's behaviour in agent negotiation},
  booktitle = {AI 2005: Advances in Artificial Intelligence},
  publisher = {Springer Berlin Heidelberg},
  year = {2005},
  editor = {Zhang, Shichao and Jarvis, Ray},
  volume = {3809},
  series = {Lecture Notes in Computer Science},
  pages = {653-663},
  doi = {10.1007/11589990\_68},
  isbn = {978-3-540-30462-3},
  owner = {Mark},
  timestamp = {2013.02.12},
  url = {http://dx.doi.org/10.1007/11589990\_68}
}

@INPROCEEDINGS{Brz06,
  author = {Brzostowski, Jakub and Kowalczyk, Ryszard},
  title = {Adaptive Negotiation with On-Line Prediction of Opponent Behaviour
        in Agent-Based Negotiations},
  booktitle = {Proceedings of the IEEE/WIC/ACM international conference on Intelligent
        Agent Technology},
  year = {2006},
  series = {IAT '06},
  pages = {263--269},
  address = {Washington, DC, USA},
  publisher = {IEEE Computer Society},
  acmid = {1194557},
  doi = {10.1109/IAT.2006.26},
  isbn = {0-7695-2748-5},
  numpages = {7},
  url = {http://dx.doi.org/10.1109/IAT.2006.26}
}

@INPROCEEDINGS{Brz06Predicting,
 author = {Brzostowski, Jakub and Kowalczyk, Ryszard},
  title = {Predicting partner's behaviour in agent negotiation},
  booktitle = {Proceedings of the fifth international joint conference on Autonomous
agents and multiagent systems},
series = {AAMAS '06},
isbn = {1-59593-303-4},
 location = {Hakodate, Japan},
  doi = {10.1145/1160633.1160697},
  year = {2006},
  pages = {355--361},
 publisher = {ACM},
  address = {New York, NY, USA},
  owner = {---},
  timestamp = {2011.07.03}
}

@ARTICLE{Bus08,
  author = {Lucian Bu\c{s}oniu and Robert Babu\v{s}ka and Bart De Schutter},
  title = {A Comprehensive Survey of Multiagent Reinforcement Learning},
  journal = {IEEE Transactions on Systems, Man, and Cybernetics Part C: Applications
        and Reviews},
  year = {2008},
  volume = {38},
  pages = {156--172},
  number = {2},
  owner = {Mark},
  timestamp = {2013.02.08}
}

@INPROCEEDINGS{Buf06,
  author = {Buffett, Scott and Comeau, Luc and Spencer, Bruce and Fleming, Michael W.},
  title = {Detecting opponent concessions in multi-issue automated negotiation},
  booktitle = {Proceedings of the 8th international conference on Electronic commerce:
        The new e-commerce: innovations for conquering current barriers,
        obstacles and limitations to conducting successful business on the
        internet},
  year = {2006},
  series = {ICEC '06},
  pages = {11--18},
  address = {New York, NY, USA},
  publisher = {ACM},
  acmid = {1151472},
  doi = {10.1145/1151454.1151472},
  isbn = {1-59593-392-1},
  keywords = {automated negotiation, learning, multi-issue negotiation, negotiation
        protocols, negotiation strategies, preferences},
  location = {Fredericton, New Brunswick, Canada},
  numpages = {8},
  url = {http://doi.acm.org/10.1145/1151454.1151472}
}

@ARTICLE{Buf07,
  author = {Scott Buffett and Bruce Spencer},
  title = {A Bayesian classifier for learning opponents' preferences in multi-object automated negotiation},
  journal = {Electronic Commerce Research and Applications },
  year = {2007},
  volume = {6},
  pages = {274 - 284},
  number = {3},
  doi = {http://dx.doi.org/10.1016/j.elerap.2006.06.008},
  issn = {1567-4223},
  keywords = {Automated negotiation},
  url = {http://www.sciencedirect.com/science/article/pii/S1567422306000445}
}

@INPROCEEDINGS{Buf05,
  author = {Buffett, Scott and Spencer, Bruce},
  title = {Learning opponents' preferences in multi-object automated negotiation},
  booktitle = {Proceedings of the 7th international conference on Electronic commerce},
  year = {2005},
  series = {ICEC '05},
  pages = {300--305},
  address = {New York, NY, USA},
  publisher = {ACM},
  acmid = {1089608},
  doi = {10.1145/1089551.1089608},
  isbn = {1-59593-112-0},
  keywords = {Bayesian classification, automated negotiation, multi-issue, preference
        elicitation, utility},
  location = {Xi'an, China},
  numpages = {6},
  url = {http://doi.acm.org/10.1145/1089551.1089608}
}

@TECHREPORT{Bui95,
  author = {Bui, Hung Hai and Venkatesh, Svetha and Kieronska, Dorota H.},
  title = {An architecture for negotiating agents that learn},
  institution = {Department of Computer Science, Curtin University of Technology,
        Perth, Australia},
  year = {1995},
  month = {Jul},
  owner = {---},
  publisher = {Citeseer},
  timestamp = {2011.07.03}
}

@ARTICLE{Bui99,
  author = {Bui, Hung Hai and Venkatesh, Svetha and Kieronska, Dorota H.},
  title = {Learning Other Agents' Preferences in Multi-agent Negotiation using
        the Bayesian Classifier},
  journal = {International Journal of Cooperative Information Systems},
  year = {1999},
  volume = {8},
  pages = {273--293},
  number = {4},
  owner = {Mark},
  timestamp = {2013.02.08}
}

@ARTICLE{Bul96,
  author = {Bulow, Jeremy and Klemperer, Paul},
  title = {Auctions Versus Negotiations},
  journal = {The American Economic Review},
  year = {1996},
  volume = {86},
  pages = {180-194},
  number = {1}
}

@INPROCEEDINGS{Cao09,
  author = {Jin-Gang Cao},
  title = {Research on electronic commerce automated negotiation in multi-agent
        system based on reinforcement learning},
  booktitle = {2009 International Conference on Machine Learning and Cybernetics},
  year = {2009},
  pages = {1419--1423},
  owner = {Mark},
  timestamp = {2013.02.08}
}

@article{Car10,
 author = {Carbonneau, R{\'e}al Andr{\'e} and Kersten, Gregory E. and Vahidov, Rustam M.},
 title = {Pairwise Issue Modeling for Negotiation Counteroffer Prediction Using Neural Networks},
 journal = {Decision Support Systems},
 issue_date = {January, 2011},
 volume = {50},
 number = {2},
 month = {Jan},
 year = {2011},
 issn = {0167-9236},
 pages = {449--459},
 numpages = {11},
 url = {http://dx.doi.org/10.1016/j.dss.2010.11.002},
 doi = {10.1016/j.dss.2010.11.002},
 acmid = {1899624},
 publisher = {Elsevier Science Publishers B. V.},
 address = {Amsterdam, The Netherlands, The Netherlands},
 keywords = {Counteroffer prediction, Electronic negotiations, Neural networks, Offer optimization, Opponent modeling, Pairwise analysis},
}

@inproceedings{Car14,
  title={What's Next? {Predicting} the Issue a Negotiator Would Choose to Concede On},
  author={Carbonneau, R{\'e}al Andr{\'e} and Vahidov, Rustam M.},
  booktitle={Group Decision and Negotiation 2014: Proceedings of the Joint International Conference of the INFORMS GDN Section and the EURO Working Group on DSS},
  pages={52},
  year={2014},
  organization={EWG-DSS}
}


@article{Car08,
 author = {Carbonneau, R{\'e}al Andr{\'e} and Kersten, Gregory E. and Vahidov, Rustam M.},
 title = {Predicting Opponent's Moves in Electronic Negotiations Using Neural Networks},
 journal = {Expert Systems with Applications},
 issue_date = {February, 2008},
 volume = {34},
 number = {2},
 month = {Feb},
 year = {2008},
 issn = {0957-4174},
 pages = {1266--1273},
 numpages = {8},
 url = {http://dx.doi.org/10.1016/j.eswa.2006.12.027},
 doi = {10.1016/j.eswa.2006.12.027},
 acmid = {1322792},
 publisher = {Pergamon Press, Inc.},
 address = {Tarrytown, NY, USA},
 keywords = {Counter-offer prediction, Electronic negotiations, Neural networks, Offer optimization, Opponent modeling},
}

@ARTICLE{Car86,
  author = {Carnevale, Peter J.D. and Lawler, Edward J.},
  title = {Time Pressure and the Development of Integrative Agreements in Bilateral     Negotiations},
  journal = {The Journal of Conflict Resolution},
  year = {1986},
  volume = {30},
  pages = {636-659},
  number = {4},
  abstract = {A laboratory experiment examined the effects of time pressure on the
        process and outcome of integrative bargaining. Time pressure was
        operationalized in terms of the amount of time available to negotiate.
        As hypothesized, high time pressure produced nonagreements and poor
        negotiation outcomes only when negotiators adopted an individualistic
        orientation; when negotiators adopted a cooperative orientation,
        they achieved high outcomes regardless of time pressure. In combination
        with an individualistic orientation, time pressure produced greater
        competitiveness, firm negotiator aspirations, and reduced information
        exchange. In combination with a cooperative orientation, time pressure
        produced greater cooperativeness and lower negotiator aspirations.
        The main findings were seen as consistent with Pruitt's strategic-choice
        model of negotiation.},
  copyright = {Copyright 1986 Sage Publications, Inc.},
  issn = {00220027},
  jstor_articletype = {research-article},
  jstor_formatteddate = {Dec., 1986},
  language = {English},
  owner = {tim},
  publisher = {Sage Publications, Inc.},
  timestamp = {2011.03.11},
  url = {http://www.jstor.org/stable/174079}
}

@incollection{Car93,
booktitle={Time Pressure and Stress in Human Judgment and Decision Making},
author={Carnevale, Peter J.D. and O'Connor, Kathleen M. and McCusker, Christopher},
year={1993},
isbn={978-1-4419-3233-4},
editor={Svenson, Ola and Maule, Alexander John},
doi={10.1007/978-1-4757-6846-6_8},
title={Time Pressure in Negotiation and Mediation},
url={http://dx.doi.org/10.1007/978-1-4757-6846-6_8},
publisher={Springer US},
pages={117-127},
language={English}
}

@INPROCEEDINGS{Cha01,
  author = {Chajewska, U. and Koller, D. and Ormoneit, D.},
  title = {Learning an Agent's Utility Function by Observing Behavior},
  booktitle = {Proceedings of the Eighteenth International Conference on Machine
        Learning},
  year = {2001},
  pages = {35--42},
  organization = {Morgan Kaufmann Publishers Inc.},
  owner = {Mark},
  timestamp = {2013.02.09}
}

@ARTICLE{Cha83,
  author = {Chatterjee, Kalyan and Samuelson, William},
  title = {Bargaining under Incomplete Information},
  journal = {Operations Research},
  year = {1983},
  volume = {31},
  pages = {835--851},
  number = {5},
  abstract = {This paper presents and analyzes a bargaining model of bilateral monopoly
        under uncertainty. Under the bargaining rule proposed, the buyer
        and the seller each submit sealed offers that determine whether the
        good in question is sold and the transfer price. The Nash equilibrium
        solution of this bargaining game implies an offer strategy of each
        party that is monotonic in its own reservation price and depends
        on its assessment of the opponent's reservation price. Issues of
        relative bargaining advantage and efficiency are examined for a number
        of special cases. Finally, we discuss the appropriateness of the
        Nash solution concept.},
  copyright = {Copyright 1983 INFORMS},
  issn = {0030364X},
  jstor_articletype = {primary article},
  jstor_formatteddate = {Sep. - Oct., 1983},
  owner = {tim},
  publisher = {INFORMS},
  timestamp = {2010.04.01},
  url = {http://www.jstor.org/stable/170889}
}

@article{Cha14,
year={1996},
issn={0926-2644},
journal={Group Decision and Negotiation},
volume={5},
number={4-6},
doi={10.1007/BF00553908},
title={Game theory and the practice of bargaining},
url={http://dx.doi.org/10.1007/BF00553908},
publisher={Kluwer Academic Publishers},
keywords={game theory; bargaining; negotiation analysis},
author={Chatterjee, Kalyan},
pages={355-369},
language={English}
}

@ARTICLE{che93,
  author = {Che, Y.K.},
  title = {Design competition through multidimensional auctions},
  journal = {RAND Journal of Economics},
  year = {1993},
  volume = {24},
  pages = {668-680},
  number = {4}
}

@ARTICLE{Che04,
  author = {Chen, C.W.},
  title = {Develop a negotiation estimation strategy for multi-issue negotiation},
  journal = {Industrial Engineering},
  year = {2004},
  owner = {Mark},
  timestamp = {2013.01.25}
}

@INPROCEEDINGS{Chen02,
  author = {Chen, Jen-Hsiang and Chao, Kuo-Ming and Godwin, Nick and Reeves, Colin and Smith, Peter},
  title = {An automated negotiation mechanism based on co-evolution and game theory},
  booktitle = {Proceedings of the 2002 ACM symposium on Applied computing},
  year = {2002},
  series = {SAC '02},
  pages = {63--67},
  address = {New York, NY, USA},
  publisher = {ACM},
  acmid = {508805},
  doi = {10.1145/508791.508805},
  isbn = {1-58113-445-2},
  keywords = {game theory, genetic algorithm, no fear of deviation, prisoner dilemma},
  location = {Madrid, Spain},
  numpages = {5},
  url = {http://doi.acm.org/10.1145/508791.508805}
}

@TECHREPORT{Che04Elicitation,
  author = {Li Chen and Pearl Pu},
  title = {Survey of Preference Elicitation Methods},
  institution = {Ecole Politechnique Federale de Lausanne (EPFL), IC/2004/67},
  year = {2004},
  owner = {Mark},
  timestamp = {2013.02.12}
}

@INPROCEEDINGS{Hai13,
  author = {Siqi Chen and Haitham Bou Ammar and Kurt Driessens and Karl Tuyls and Gerhard Weiss},
  title = {Automatic Transfer Between Negotiation Tasks},
  booktitle = {Proceedings of the Adaptive Learning Agents (ALA) at International
        Conference on Autonomous Agents and Multi Agent Systems (AAMAS)},
  year = {2013},
  address = {Minnesota, USA}
}

@INPROCEEDINGS{Chen13,
  author = {Chen, Siqi and Ammar, Haitham Bou and Tuyls, Karl and Weiss, Gerhard},
  title = {Optimizing Complex Automated Negotiation Using Sparse Pseudo-input Gaussian Processes},
  booktitle = {Proceedings of the 2013 International Conference on Autonomous Agents and Multi-agent Systems},
  year = {2013},
  series = {AAMAS '13},
  pages = {707--714},
  address = {Richland, SC},
  publisher = {International Foundation for Autonomous Agents and Multiagent Systems},
  acmid = {2485032},
  isbn = {978-1-4503-1993-5},
  keywords = {automated multi-issue negotiation, empirical game theory, multi-agent
        systems, opponent modeling, sparse gaussian process},
  location = {St. Paul, MN, USA},
  numpages = {8},
  url = {http://dl.acm.org/citation.cfm?id=2484920.2485032}
}

@incollection{Chen14,
  title={Evaluating practical automated negotiation based on spatial evolutionary game theory},
  author={Chen, Siqi and Hao, Jianye and Weiss, Gerhard and Tuyls, Karl and Leung, {Ho-fung}},
booktitle={KI 2014: Advances in Artificial Intelligence},
volume={8736},
series={Lecture Notes in Computer Science},
editor={Lutz, Carsten and Thielscher, Michael},
pages={147--158},
  year={2014},
  doi={10.1007/978-3-319-11206-0_15},
  url={http://dx.doi.org/10.1007/978-3-319-11206-0_15},
publisher={Springer International Publishing},
  isbn={978-3-319-11205-3}
}

@INPROCEEDINGS{Hai12,
  author = {Siqi Chen and Haitham Bou Ammar and Karl Tuyls and Gerhard Weiss},
  title = {Transfer Learning for Bilateral Multi Issue Negotiation},
  booktitle = {Proceedings of the Benelux Conference on Artificial Intelligence (BNAIC)},
  year = {2012},
  address = {Maastricht, The Netherlands}
}

@INPROCEEDINGS{Che12OMAC,
  author = {Chen, Siqi and Weiss, Gerhard},
  title = {An Efficient and Adaptive Approach to Negotiation in Complex Environments},
  booktitle = {ECAI},
  year = {2012},
  editor = {Raedt, Luc De and Bessiere, Christian and Dubois, Didier and Doherty,
        Patrick and Frasconi, Paolo and Heintz, Fredrik and Lucas, Peter J.F.},
  volume = {242},
  series = {Frontiers in Artificial Intelligence and Applications},
  pages = {228-233},
  publisher = {IOS Press},
  added-at = {2012-09-06T00:00:00.000+0200},
  biburl = {http://www.bibsonomy.org/bibtex/28f3e1fd201065920b9a2dc5f8f2acd77/dblp},
  ee = {http://dx.doi.org/10.3233/978-1-61499-098-7-228},
  interhash = {0112ddb6c6508e734f8821d86681969e},
  intrahash = {8f3e1fd201065920b9a2dc5f8f2acd77},
  isbn = {978-1-61499-097-0},
  keywords = {dblp},
  timestamp = {2012-09-06T00:00:00.000+0200},
  url = {http://dblp.uni-trier.de/db/conf/ecai/ecai2012.html#ChenW12}
}

@incollection{Che12OMACAgent,
        year={2014},
        isbn={978-4-431-54757-0},
        booktitle={Novel Insights in Agent-based Complex Automated Negotiation},
        volume={535},
        series={Studies in Computational Intelligence},
        editor={Marsa-Maestre, Ivan and Lopez-Carmona, Miguel A. and Ito, Takayuki and Zhang, Minjie and Bai, Quan and Fujita, Katsuhide},
        doi={10.1007/978-4-431-54758-7_13},
        title={{OMAC}: A Discrete Wavelet Transformation Based Negotiation Agent},
        url={http://dx.doi.org/10.1007/978-4-431-54758-7_13},
        publisher={Springer Japan},
        keywords={Automated multi-issue negotiation; Discrete wavelet transformation; Opponent modeling},
        author={Chen, Siqi and Weiss, Gerhard},
        pages={187-196},
        language={English}
}

@INCOLLECTION{Che12,
  author = {Chen, Siqi and Weiss, Gerhard},
  title = {A Novel Strategy for Efficient Negotiation in Complex Environments},
  booktitle = {Multiagent System Technologies},
  publisher = {Springer Berlin Heidelberg},
  year = {2012},
  editor = {Timm, Ingo J. and Guttmann, Christian},
  volume = {7598},
  series = {Lecture Notes in Computer Science},
  pages = {68-82},
  doi = {10.1007/978-3-642-33690-4\_8},
  isbn = {978-3-642-33689-8},
  owner = {Mark},
  timestamp = {2013.02.12},
  url = {http://dx.doi.org/10.1007/978-3-642-33690-4\_8}
}

@ARTICLE{Che13Strategy,
  author = {Siqi Chen and Gerhard Weiss},
  title = {An efficient automated negotiation strategy for complex environments
        },
  journal = {Engineering Applications of Artificial Intelligence },
  year = {2013},
  doi = {http://dx.doi.org/10.1016/j.engappai.2013.08.012},
  issn = {0952-1976},
  url = {http://www.sciencedirect.com/science/article/pii/S0952197613001693}
}

@ARTICLE{Che06,
  author = {Chi-Bin Cheng and Chu-Chai Henry Chan and Kun-Cheng Lin},
  title = {Intelligent agents for e-marketplace: Negotiation with issue trade-offs
        by fuzzy inference systems},
  journal = {Decision Support Systems},
  year = {2006},
  volume = {42},
  pages = {626 - 638},
  number = {2},
  abstract = {Automated negotiation by autonomous agents has become increasingly
        important since the advent of e-marketplace. In this study, automated
        negotiation is viewed as a search process in which negotiators jointly
        search for a mutually acceptable contract in a multidimensional space
        formed by negotiable issues. This search is formulated as a multiple-objective
        decision making problem and is solved through an iterative process
        of generating offers by fuzzy inference systems. These fuzzy inference
        systems serve as a search heuristic and are formulated based on the
        strategy of issue trade-offs. Five experiments are conducted to evaluate
        the performance of the proposed automated negotiation algorithm.},
  doi = {10.1016/j.dss.2005.02.009},
  issn = {0167-9236},
  keywords = {Automated negotiation},
  owner = {tim},
  timestamp = {2012.02.14},
  url = {http://www.sciencedirect.com/science/article/pii/S0167923605000527}
}

@ARTICLE{Cho01,
  author = {Samuel P.M. Choi and Jiming Liu and Sheung-Ping Chan},
  title = {A genetic agent-based negotiation system},
  journal = {Computer Networks},
  year = {2001},
  volume = {37},
  pages = {195 - 204},
  number = {2},
  issn = {1389-1286},
  owner = {Mark},
  timestamp = {2013.02.08}
}

@INPROCEEDINGS{Cle03,
  author = {Clement, Bradley J. and Barrett, Anthony C.},
  title = {Continual coordination through shared activities},
  booktitle = {Proceedings of the second international joint conference on Autonomous
        agents and multiagent systems},
  year = {2003},
  series = {AAMAS '03},
  pages = {57--64},
  address = {New York, NY, USA},
  publisher = {ACM},
  acmid = {860585},
  doi = {10.1145/860575.860585},
  isbn = {1-58113-683-8},
  keywords = {communication protocols, coordination, multiagent planning},
  location = {Melbourne, Australia},
  numpages = {8},
  url = {http://doi.acm.org/10.1145/860575.860585}
}

@INPROCEEDINGS{Coe02,
  author = {Coe, Robert},
  title = {It's the effect size, stupid: What effect size is and why it is important},
  booktitle = {British Educational Research Association Conference},
  year = {2002},
  publisher = {Education-line}
}

@INPROCEEDINGS{Coe04,
  author = {Coehoorn, Robert M. and Jennings, Nicholas R.},
  title = {Learning an opponent's preferences to make effective multi-issue     negotiation trade-offs},
  booktitle = {Proceedings of the 6th international conference on Electronic commerce},
  year = {2004},
  series = {ICEC '04},
  pages = {59--68},
  address = {New York, NY, USA},
  publisher = {ACM},
  acmid = {1052229},
  doi = {10.1145/1052220.1052229},
  isbn = {1-58113-930-6},
  location = {Delft, The Netherlands},
  numpages = {10},
  url = {http://doi.acm.org/10.1145/1052220.1052229}
}

@INPROCEEDINGS{Coe04short,
  author = {Coehoorn, Robert M. and Jennings, Nicholas R.},
  title = {Learning an opponent's preferences to make effective multi-issue
        negotiation trade-offs},
  booktitle = {Proceedings of the 6th international conference on Electronic commerce},
  year = {2004},
  acmid = {1052229},
  isbn = {1-58113-930-6},
  location = {Delft, The Netherlands},
  numpages = {10},
  owner = {Mark},
  timestamp = {2013.04.20}
}

@INPROCEEDINGS{Com99,
  author = {Comaniciu, D. and Meer, P.},
  title = {Mean shift analysis and applications},
  booktitle = {Proceedings of the Seventh IEEE International Conference on Computer
        Vision},
  year = {1999},
  volume = {2},
  pages = {1197--1203},
  organization = {Ieee},
  owner = {---},
  timestamp = {2011.07.02}
}

@ARTICLE{Cra07,
  author = {Crawford, Elisabeth and Veloso, Manuela},
  title = {An experts approach to strategy selection in multiagent meeting scheduling},
  journal = {Autonomous Agents and Multi-Agent Systems},
  year = {2007},
  volume = {15},
  pages = {5-28},
  affiliation = {Carnegie Mellon University Computer Science Department Pittsburgh
        PA 15213 USA Pittsburgh PA 15213 USA},
  issn = {1387-2532},
  issue = {1},
  keyword = {Computer Science},
  owner = {Mark},
  publisher = {Springer Netherlands},
  timestamp = {2013.02.08}
}

@ARTICLE{Cro65,
  author = {John G. Cross},
  title = {A theory of the bargaining process},
  journal = {The American Economic Review},
  year = {1965},
  volume = {55},
  pages = {67-94},
  owner = {tim},
  timestamp = {2010.03.12},
  url = {http://www.jstor.org/stable/1816177}
}

@MISC{Dav02,
  author = {David, E and Azoulay-Schwartz, R. and Kraus, S.},
  title = {Protocols and strategies for automated multi-attribute auctions},
  year = {2002},
  pages = {77-85}
}

@BOOK{DeG70,
  title = {Optimal statistical decisions},
  publisher = {McGraw-Hill},
  year = {1970},
  author = {DeGroot, {Morris H.}},
  address = {New York, NY, USA},
  added-at = {2009-08-21T12:29:29.000+0200},
  biburl = {http://www.bibsonomy.org/bibtex/24774fe9b324b9ae13c6dc2a42b01d3d0/fbw\_hannover},
  interhash = {ead141651f4a614621e49992a69f9bb9},
  intrahash = {4774fe9b324b9ae13c6dc2a42b01d3d0},
  isbn = {0070162425},
  keywords = {Mathematische Statistik Statistische Entscheidungstheorie},
  pagetotal = {XVI, 489},
  ppn_gvk = {021834997},
  timestamp = {2009-08-21T12:29:29.000+0200},
  url = {http://gso.gbv.de/DB=2.1/CMD?ACT=SRCHA\&SRT=YOP\&IKT=1016\&TRM=ppn+021834997\&sourceid=fbw\_bibsonomy}
}

@ARTICLE{Del97,
  author = {Michael M. Delaney and Abbas Foroughi and William C. Perkins},
  title = {An empirical study of the efficacy of a computerized negotiation     support system {(NSS)}},
  journal = {Decision Support Systems },
  year = {1997},
  volume = {20},
  pages = {185 - 197},
  number = {3},
  abstract = {This paper presents the results of an empirical study to investigate
        the effects of a computerized \{NSS\} on the outcomes of face-to-face
        negotiations and on negotiator attitudes. In the study, pairs (dyads)
        of college students were involved in a simulated industrial bargaining
        scenario which tested the impact of computer support and conflict
        level on contract outcomes and negotiator attitudes. Three levels
        of computer support were compared: a comprehensive \{NSS\} (DSS component
        and an electronic communication component), \{DSS\} support only
        (no electronic communication component), and no computer support.
        The results showed that the \{DSS\} support was similar to the comprehensive
        \{NSS\} in improving the information processing aspects of the negotiation,
        such as joint outcomes, contract balance, and number of contract
        proposals. However, the comprehensive \{NSS\} had a wider spectrum
        of positive effects, impacting the socio-emotional aspects of the
        negotiation such as perceived satisfaction and negative climate as
        well as the information processing aspects. },
  doi = {http://dx.doi.org/10.1016/S0167-9236(96)00051-6},
  issn = {0167-9236},
  keywords = {Negotiation support systems},
  url = {http://www.sciencedirect.com/science/article/pii/S0167923696000516}
}

@BOOK{Deu00,
  title = {The Handbook of Conflict Resolution: Theory and Practice},
  publisher = {Jossey-Bass},
  year = {2000},
  author = {Deutsch, Morton and Coleman, Peter T. and Marcus, Eric Colton},
  edition = {1st},
  month = {Apr},
  abstract = {{Morton Deutsch, one of the world's most respected figures in conflict
        resolution, and Peter T. Coleman, a prominent scholar in this field,
        have brought together a diverse group of experts to create a comprehensive
        resource that integrates theory and practice. Drawing on a vast range
        of knowledge, this groundbreaking book contains the most authoritative
        research, definitive examples, and up-to-date information available.
        Written for professionals and students in the wide variety of conflict
        resolution fields, this essential resource offers clear directions
        for creating constructive solutions to challenging interpersonal,
        intergroup, and international conflict.}},
  citeulike-article-id = {4487832},
  citeulike-linkout-0 = {http://www.amazon.ca/exec/obidos/redirect?tag=citeulike09-20\&path=ASIN/0787948225},
  citeulike-linkout-1 = {http://www.amazon.de/exec/obidos/redirect?tag=citeulike01-21\&path=ASIN/0787948225},
  citeulike-linkout-2 = {http://www.amazon.fr/exec/obidos/redirect?tag=citeulike06-21\&path=ASIN/0787948225},
  citeulike-linkout-3 = {http://www.amazon.jp/exec/obidos/ASIN/0787948225},
  citeulike-linkout-4 = {http://www.amazon.co.uk/exec/obidos/ASIN/0787948225/citeulike00-21},
  citeulike-linkout-5 = {http://www.amazon.com/exec/obidos/redirect?tag=citeulike07-20\&path=ASIN/0787948225},
  citeulike-linkout-6 = {http://www.worldcat.org/isbn/0787948225},
  citeulike-linkout-7 = {http://books.google.com/books?vid=ISBN0787948225},
  citeulike-linkout-8 = {http://www.amazon.com/gp/search?keywords=0787948225\&index=books\&linkCode=qs},
  citeulike-linkout-9 = {http://www.librarything.com/isbn/0787948225},
  day = {15},
  howpublished = {Hardcover},
  isbn = {0787948225},
  owner = {tim},
  posted-at = {2009-05-07 19:35:02},
  priority = {2},
  timestamp = {2011.06.22},
  url = {http://www.worldcat.org/isbn/0787948225}
}

@ARTICLE{Dev01,
  author = {Laurent Devaux and Corina Paraschiv},
  title = {Bargaining on an Internet Agent-based Market: Behavioral vs. Optimizing
        Agents},
  journal = {Electronic Commerce Research},
  year = {2001},
  volume = {1},
  pages = {371-401}
}

@INPROCEEDINGS{Cos08,
  author = {Diniz Da Costa, Andrew and Lucena, Carlos J. and Torres Da Silva,
        Viviane and Azevedo, S\'{e}rgio C. and Soares, F\'{a}bio A.},
  title = {Art Competition: Agent Designs to Handle Negotiation Challenges},
  booktitle = {Trust in Agent Societies: 11th International Workshop, TRUST 2008,
        Estoril, Portugal, May 12 -13, 2008. Revised Selected and Invited
        Papers},
  year = {2008},
  pages = {244--272},
  address = {Berlin, Heidelberg},
  publisher = {Springer-Verlag},
  doi = {http://dx.doi.org/10.1007/978-3-540-92803-4\_13},
  isbn = {978-3-540-92802-7},
  owner = {tim},
  timestamp = {2010.07.29}
}

@mastersthesis{DirThesis,
  title={Towards Understanding Negotiation Strategies: Analyzing the Dynamics of Strategy Components},
  author={Dirkzwager, A.S.Y.},
  year={2013},
  school={Delft University of Technology}
}

@INCOLLECTION{ANAC2011Dir,
  author = {Dirkzwager, A.S.Y. and Hendrikx, M.J.C. and Ruiter, J.R.},
  title = {The {N}egotiator: A Dynamic Strategy for Bilateral Negotiations with
        Time-Based Discounts},
  booktitle = {Complex Automated Negotiations: Theories, Models, and Software Competitions},
  publisher = {Springer Berlin Heidelberg},
  year = {2013},
  editor = {Ito, Takayuki and Zhang, Minjie and Robu, Valentin and Matsuo, Tokuro},
  volume = {435},
  series = {Studies in Computational Intelligence},
  pages = {217-221},
  doi = {10.1007/978-3-642-30737-9\_16},
  isbn = {978-3-642-30736-2},
  url = {http://dx.doi.org/10.1007/978-3-642-30737-9\_16}
}

@INCOLLECTION{ANAC2011Dirshort,
  author = {Dirkzwager, A.S.Y. and Hendrikx, M.J.C. and Ruiter, J.R.},
  title = {The Negotiator: A Dynamic Strategy for Bilateral Negotiations with
        Time-Based Discounts},
  booktitle = {Complex Automated Negotiations: Theories, Models, and Software Competitions},
  publisher = {Springer Berlin Heidelberg},
  year = {2013},
  pages = {217-221},
  doi = {10.1007/978-3-642-30737-9\_16},
  isbn = {978-3-642-30736-2},
  url = {http://dx.doi.org/10.1007/978-3-642-30737-9\_16}
}

@INCOLLECTION{ANAC2011Dirshorter,
  author = {Dirkzwager, A.S.Y. and Hendrikx, M.J.C. and Ruiter, J.R.},
  title = {The Negotiator: A Dynamic Strategy for Bilateral Negotiations with
        Time-Based Discounts},
  booktitle = {Complex Automated Negotiations: Theories, Models, and Software Competitions},
  publisher = {Springer Berlin Heidelberg},
  year = {2013},
  isbn = {978-3-642-30736-2},
  owner = {Mark},
  timestamp = {2013.04.20}
}

@ARTICLE{Dra95,
  author = {Drake, L.E.},
  title = {Negotiation styles in intercultural communication},
  journal = {International Journal of Conflict Management},
  year = {1995},
  volume = {6},
  pages = {72--90},
  number = {1},
  owner = {Mark},
  publisher = {MCB UP Ltd},
  timestamp = {2012.01.08}
}

@ARTICLE{Dru08,
  author = {Druckman, Daniel and Olekalns, Mara},
  title = {Emotions in negotiation},
  journal = {Group Decision and Negotiation},
  year = {2008},
  volume = {17},
  pages = {1--11},
  number = {1},
  doi = {10.1007/s10726-007-9091-9},
  issn = {0926-2644},
  keywords = {Emotions; Experimentation; Expression games; Information-processing;
        Intentions; Negotiation},
  language = {English},
  owner = {Mark},
  publisher = {Springer Netherlands},
  timestamp = {2012.01.08}
}

@ARTICLE{Dum02,
  author = {Dumas, M. and Governatori, G. and Ter Hofstede, A.H.M. and Oaks,
        P.},
  title = {A formal approach to negotiating agents development},
  journal = {Electronic Commerce Research and Applications},
  year = {2002},
  volume = {1},
  pages = {193--207},
  number = {2},
  owner = {Mark},
  publisher = {Elsevier},
  timestamp = {2012.02.05}
}

@ARTICLE{Dye92,
  author = {Dyer, James S. and Fishburn, Peter C. and Steuer, Ralph E. and Wallenius,
        Jyrki and Zionts, Stanley},
  title = {Multiple Criteria Decision Making, Multiattribute Utility Theory:
        The Next Ten Years},
  journal = {Management Science},
  year = {1992},
  volume = {38},
  pages = {645-654},
  number = {5}
}

@ARTICLE{Dze05,
  author = {Dzeng, Ren-Jye and Lin, Yu-Chun},
  title = {Searching for Better Negotiation Agreement Based on Genetic Algorithm},
  journal = {Computer-Aided Civil and Infrastructure Engineering},
  year = {2005},
  volume = {20},
  pages = {280--293},
  number = {4},
  doi = {10.1111/j.1467-8667.2005.00393},
  issn = {1467-8667},
  publisher = {Blackwell Publishing, Inc.},
  url = {http://dx.doi.org/10.1111/j.1467-8667.2005.00393}
}

@ARTICLE{Erev1998,
  author = {I. Erev and A. Roth},
  title = {Predicting how people play games: Reinforcement learning in experimental
        games with unique, mixed strategy equilibrium},
  journal = {American Economic Review},
  year = {1998},
  volume = {88},
  pages = {848-881},
  number = {4}
}

@INPROCEEDINGS{Eym01,
  author = {Eymann, Torsten},
  title = {Co-evolution of bargaining strategies in a decentralized multi-agent system},
  booktitle = {AAAI fall 2001 symposium on negotiation methods for autonomous cooperative systems},
  year = {2001},
  pages = {126--134},
  owner = {Mark},
  timestamp = {2012.02.19}
}

@INPROCEEDINGS{Fab10,
  author = {Fabregues, Angela and Navarro, David and Serrano, Alejandro and Sierra,     Carles},
  title = {{DipGame}: A Testbed for Multiagent Systems},
  booktitle = {Proceedings of the 9th International Conference on Autonomous Agents     and Multiagent Systems},
  year = {2010},
  volume = {1},
  series = {AAMAS '10},
  pages = {1619--1620},
  address = {Richland, SC},
  publisher = {International Foundation for Autonomous Agents and Multiagent Systems},
  acmid = {1838510},
  isbn = {978-0-9826571-1-9},
  keywords = {application, diplomacy game, testbed},
  location = {Toronto, Canada},
  numpages = {2},
  url = {http://dl.acm.org/citation.cfm?id=1838206.1838510}
}

@ARTICLE{Fab11,
  author = {Fabregues, Angela and Sierra, Carles},
  title = {{DipGame}: a challenging negotiation testbed},
  journal = {Engineering Applications of Artificial Intelligence},
  year = {2011},
  volume = {24},
  pages = {1137--1146},
  number = {7},
  publisher = {Elsevier}
}

@Article{Fab12,
  author    = {Fabregues Vinent, Angela and others},
  title     = {Facing the Challenge of Automated Negotiation with Humans},
  year      = {2012},
  publisher = {Universitat Aut{\`o}noma de Barcelona},
}

@ARTICLE{Fan08,
  author = {Fang Fang and Ye Xin and Xia Yun and Xu Haitao},
  title = {An Opponent's Negotiation Behavior Model to Facilitate Buyer-seller
        Negotiations in Supply Chain Management},
  journal = {Electronic Commerce and Security, International Symposium},
  year = {2008},
  month={Aug}, 
  pages = {582-587},
  address = {Los Alamitos, CA, USA},
  doi = {http://doi.ieeecomputersociety.org/10.1109/ISECS.2008.93},
  isbn = {978-0-7695-3258-5},
  owner = {Mark},
  publisher = {IEEE Computer Society},
  timestamp = {2013.06.12}
}

@INPROCEEDINGS{Far10,
  author = {Farag, George M. and AbdelRahman, Samir El-Sayed and Bahgat, Reem and A-Moneim,
        Atef M.},
  title = {Towards {KDE} mining approach for multi-agent negotiation},
  booktitle = {Informatics and Systems (INFOS), 2010 The 7th International Conference
        on},
  year = {2010},
  month={Mar}, 
  pages = {1--7},
  organization = {IEEE},
  owner = {Mark},
  timestamp = {2012.06.30}
}

@INPROCEEDINGS{Far10Estimating,
  author = {Farag, G.M. and AbdelRahman, S.E.S. and Bahgat, R. and A-Moneim,
        A.M.},
  title = {Estimating negotiation agreement zone using support vector machine
        with genetic algorithm},
  booktitle = {Informatics and Systems (INFOS), 2010 The 7th International Conference
        on},
  year = {2010},
  pages = {1--8},
  organization = {IEEE},
  owner = {Mark},
  timestamp = {2013.02.09}
}

@ARTICLE{Far03,
  author = {Peyman Faratin and Carles Sierra and Nicholas R. Jennings},
  title = {Using similarity criteria to make issue trade-offs in automated negotiations},
  journal = {Artificial Intelligence },
  year = {2002},
  volume = {142},
  pages = {205 - 237},
  number = {2},
  abstract = {Automated negotiation is a key form of interaction in systems that
        are composed of multiple autonomous agents. The aim of such interactions
        is to reach agreements through an iterative process of making offers.
        The content of such proposals are, however, a function of the strategy
        of the agents. Here we present a strategy called the trade-off strategy
        where multiple negotiation decision variables are traded-off against
        one another (e.g., paying a higher price in order to obtain an earlier
        delivery date or waiting longer in order to obtain a higher quality
        service). Such a strategy is commonly known to increase the social
        welfare of agents. Yet, to date, most computational work in this
        area has ignored the issue of trade-offs, instead aiming to increase
        social welfare through mechanism design. The aim of this paper is
        to develop a heuristic computational model of the trade-off strategy
        and show that it can lead to an increased social welfare of the system.
        A novel linear algorithm is presented that enables software agents
        to make trade-offs for multi-dimensional goods for the problem of
        distributed resource allocation. Our algorithm is motivated by a
        number of real-world negotiation applications that we have developed
        and can operate in the presence of varying degrees of uncertainty.
        Moreover, we show that on average the total time used by the algorithm
        is linearly proportional to the number of negotiation issues under
        consideration. This formal analysis is complemented by an empirical
        evaluation that highlights the operational effectiveness of the algorithm
        in a range of negotiation scenarios. The algorithm itself operates
        by using the notion of fuzzy similarity to approximate the preference
        structure of the other negotiator and then uses a hill-climbing technique
        to explore the space of possible trade-offs for the one that is most
        likely to be acceptable. },
  doi = {10.1016/S0004-3702(02)00290-4},
  issn = {0004-3702},
  keywords = {Multi agent systems},
  url = {http://www.sciencedirect.com/science/article/pii/S0004370202002904}
}

@TECHREPORT{Far99,
  author = {Peyman Faratin and Carles Sierra and Nicholas R. Jennings and Philip Buckle},
  title = {Designing flexible automated negotiators: Concessions, trade-offs and issue changes},
  institution = {Instituto de Investigaci\'{o}n en Inteligencia Artificial},
  year = {1999},
  owner = {tim},
  timestamp = {2011.05.31}
}

@ARTICLE{Far98,
  author = {Peyman Faratin and Carles Sierra and Nicholas R. Jennings},
  title = {Negotiation decision functions for autonomous agents },
  journal = {Robotics and Autonomous Systems},
  year = {1998},
  volume = {24},
  pages = {159 - 182},
  number = {3-4},
  abstract = {We present a formal model of negotiation between autonomous agents.
        The purpose of the negotiation is to reach an agreement about the
        provision of a service by one agent for another. The model defines
        a range of strategies and tactics that agents can employ to generate
        initial offers, evaluate proposals and offer counter proposals. The
        model is based on computationally tractable assumptions, demonstrated
        in the domain of business process management and empirically evaluated.},
  doi = {10.1016/S0921-8890(98)00029-3},
  issn = {0921-8890},
  keywords = {Multi-agent systems},
  url = {http://www.sciencedirect.com/science/article/pii/S0921889098000293}
}

@ARTICLE{Far98short,
  author = {Peyman Faratin and Carles Sierra and Nicholas R. Jennings},
  title = {Negotiation decision functions for autonomous agents },
  journal = {Robotics and Autonomous Systems},
  year = {1998},
  volume = {24},
  pages = {159 - 182},
  number = {3-4},
  abstract = {We present a formal model of negotiation between autonomous agents.
        The purpose of the negotiation is to reach an agreement about the
        provision of a service by one agent for another. The model defines
        a range of strategies and tactics that agents can employ to generate
        initial offers, evaluate proposals and offer counter proposals. The
        model is based on computationally tractable assumptions, demonstrated
        in the domain of business process management and empirically evaluated.
        },
  doi = {10.1016/S0921-8890(98)00029-3},
  issn = {0921-8890},
  keywords = {Multi-agent systems}
}

@INPROCEEDINGS{Fat04Incomplete,
  author = {Fatima, Shaheen and Wooldridge, Michael J. and Jennings, Nicholas R.},
  title = {Optimal negotiation of multiple issues in incomplete information
        settings},
  booktitle = {Proceedings of the Third International Joint Conference on Autonomous
        Agents and Multiagent Systems},
  year = {2004},
  volume = {3},
  pages = {1080--1087},
  organization = {IEEE Computer Society},
  owner = {---},
  timestamp = {2011.08.17}
}

@INPROCEEDINGS{Fat03,
  author = {Fatima, Shaheen S. and Wooldridge, Michael J. and Jennings, Nicholas R.},
  title = {Optimal agendas for multi-issue negotiation},
  booktitle = {Proceedings of the second international joint conference on Autonomous
        agents and multiagent systems},
         series = {AAMAS '03},
          location = {Melbourne, Australia},
  year = {2003},
   isbn = {1-58113-683-8},
    publisher = {ACM},
 address = {New York, NY, USA},
  pages = {129--136},
   doi = {10.1145/860575.860597},
  owner = {Mark},
  timestamp = {2012.01.08}
}

@MISC{Fat09,
  author = {Fatima, Shaheen S. and Wooldridge, Michael J. and Jennings, Nicholas R.},
  title = {An analysis of feasible solutions for multi-issue negotiation involving
        nonlinear utility functions},
  year = {2009},
  acmid = {1558158},
  address = {Richland, SC},
  booktitle = {Proceedings of The 8th International Conference on Autonomous Agents
        and Multiagent Systems},
        volume = {2},
  isbn = {978-0-9817381-7-8},
  keywords = {approximation, game-theory, negotiation},
  location = {Budapest, Hungary},
  numpages = {8},
  pages = {1041--1048},
  publisher = {International Foundation for Autonomous Agents and Multiagent Systems},
  series = {AAMAS '09},
  url = {http://portal.acm.org/citation.cfm?id=1558109.1558158}
}

@ARTICLE{Fat07,
  author = {Fatima, Shaheen S. and Wooldridge, Michael J. and Jennings, Nicholas R.},
  title = {On efficient procedures for multi-issue negotiation},
  journal = {Agent-Mediated Electronic Commerce},
  year = {2007},
  volume = {4452},
  pages = {31-45 249},
  abstract = {This paper studies bilateral, multi-issue negotiation between self
        interested agents with deadlines. There are a number of procedures
        for negotiating the issues and each of these gives a different outcome.
        Thus, a key problem is to decide which one to use. Given this, we
        study the three main alternatives: the package deal, the simultaneous
        procedure, and the sequential procedure. First, we determine equilibria
        for the case where each agent is uncertain about its opponent's deadline.
        We then compare the outcomes for these procedures and determine the
        one that is optimal (in this case, the package deal is optimal for
        each party). We then compare the procedures in terms of their time
        complexity, the uniqueness and Pareto optimality of their solutions,
        and their time of agreement.},
  keywords = {agenda}
}

@ARTICLE{Fat06,
  author = {Fatima, Shaheen S. and Wooldridge, Michael J. and Jennings, Nicholas R.},
  title = {Multi-issue negotiation with deadlines},
  journal = {Journal of Artificial Intelligence Research},
  year = {2006},
  volume = {27},
  pages = {381-417},
  abstract = {This paper studies bilateral multi-issue negotiation between self-interested
        autonomous agents. Now, there are a number of different procedures
        that can be used for this process; the three main ones being the
        package deal procedure in which all the issues are bundled and discussed
        together, the simultaneous procedure in which the issues are discussed
        simultaneously but independently of each other, and the sequential
        procedure in which the issues are discussed one after another. Since
        each of them yields a different outcome, a key problem is to decide
        which one to use in which circumstances. Specifically, we consider
        this question for a model in which the agents have time constraints
        ( in the form of both deadlines and discount factors) and information
        uncertainty ( in that the agents do not know the opponent's utility
        function). For this model, we consider issues that are both independent
        and those that are interdependent and determine equilibria for each
        case for each procedure. In so doing, we show that the package deal
        is in fact the optimal procedure for each party. We then go on to
        show that, although the package deal may be computationally more
        complex than the other two procedures, it generates Pareto optimal
        outcomes ( unlike the other two), it has similar earliest and latest
        possible times of agreement to the simultaneous procedure ( which
        is better than the sequential procedure), and that it ( like the
        other two procedures) generates a unique outcome only under certain
        conditions ( which we define).},
  keywords = {interdependent preferences incomplete information bargaining model
        agenda equilibrium}
}

@ARTICLE{Fat05,
  author = {Fatima, Shaheen S. and Wooldridge, Michael J. and Jennings, Nicholas R.},
  title = {A Comparative Study of Game Theoretic and Evolutionary Models of     Bargaining for Software Agents},
  journal = {Artificial Intelligence Review},
  year = {2005},
  volume = {23},
  pages = {187-205},
  doi={10.1007/s10462-004-6391-1},
  publisher={Kluwer Academic Publishers},
  issn={0269-2821},
  number = {2}
}

@ARTICLE{Fat04,
  author = {Fatima, Shaheen S. and Wooldridge, Michael J. and Jennings, Nicholas R.},
  title = {An agenda-based framework for multi-issue negotiation},
  journal = {Artificial Intelligence},
  year = {2004},
  volume = {152},
  pages = {1-45},
  number = {1},
  abstract = {This paper presents a new model for multi-issue negotiation under
        time constraints in an incomplete information setting. The issues
        to be bargained over can be associated with a single good/service
        or multiple goods/services. In our agenda-based model, the order
        in which issues are bargained over and agreements are reached is
        determined endogenously, as part of the bargaining equilibrium. In
        this context we determine the conditions under which agents have
        similar preferences over the implementation scheme and the conditions
        under which they have conflicting preferences. Our analysis shows
        the existence of equilibrium even when both players have uncertain
        information about each other, and each agent's information is its
        private knowledge. We also study the properties of the equilibrium
        solution and determine conditions under which it is unique, symmetric,
        and Pareto-optimal. (C) 2003 Elsevier B.V. All rights reserved.},
  keywords = {multi-issue negotiation game theory agendas intelligent agents incomplete
        information bargaining model time preference equilibrium}
}

@INPROCEEDINGS{Fat02,
    author = {Fatima, Shaheen S. and Wooldridge, Michael J. and Jennings, Nicholas R.},
  title = {Multi-issue negotiation under time constraints},
  booktitle = {AAMAS '02: Proceedings of the first international joint conference
        on Autonomous agents and multiagent systems},
  year = {2002},
  pages = {143--150},
  address = {New York, NY, USA},
  publisher = {ACM},
  doi = {http://doi.acm.org/10.1145/544741.544775},
  isbn = {1-58113-480-0},
  location = {Bologna, Italy},
  owner = {tim}
}

@ARTICLE{Fat02inf,
    author = {Fatima, Shaheen S. and Wooldridge, Michael J. and Jennings, Nicholas R.},
  title = {The influence of information on negotiation equilibrium},
  journal = {Agent-Mediated Electronic Commerce},
  year = {2002},
  volume = {2531},
  pages = {180-193},
  abstract = {This paper studies the influence of the agents' information states
        on the negotiation equilibrium. This is undertaken by examining a
        range of negotiation scenarios in which the amount of information
        that agents have about their opponent's parameters is systematically
        varied. For each such scenario, we show that a unique equilibrium
        exists and investigate how the information states of agents influence
        the distribution property of the equilibrium solution. Our study
        shows the relative impacts of the opponent's parameters on the negotiation
        outcome. The results obtained are useful for decision making in situations
        where an agent has the option of choosing whom to negotiate with,
        from among a set of bargainers, on the basis of its information state.
        They also indicate which of its opponent's parameters an agent should
        learn in order to maximize its utility.},
  keywords = {bargaining model}
}

@INPROCEEDINGS{Fat02opt,
  author = {Fatima, Shaheen S. and Wooldridge, Michael J. and Jennings, Nicholas R.},
  title = {Optimal Negotiation Strategies for Agents with Incomplete Information},
  booktitle = {Revised Papers from the 8th International Workshop on Intelligent Agents VIII},
  year = {2002},
  series = {ATAL '01},
  pages = {377--392},
  address = {London, UK},
  publisher = {Springer-Verlag},
  abstract = {This paper analyzes the process of automated negotiation between two
        competitive agents that have firm deadlines and incomplete information
        about their opponent. Generally speaking, the outcome of a negotiation
        depends on many parameters-including the agents' preferences, their
        reservation limits, their attitude toward time and the strategies
        they use. Although in most realistic situations it is not possible
        for agents to have complete information about each of these parameters
        for its opponent, it is not uncommon for agents to have partial information
        about some of them. Under such uncertainty, our aim is to determine
        how an agent can exploit its available information to select an optimal
        strategy. Here, in particular, the optimal strategies are determined
        considering all possible ways in which time can effect negotiation.
        Moreover, we list the conditions for convergence when both agents
        use their respective optimal strategies and study the effect of time
        on negotiation outcome.},
  acmid = {757345},
  isbn = {3-540-43858-0},
  numpages = {16},
  url = {http://dl.acm.org/citation.cfm?id=648208.757345}
}

@ARTICLE{Fav94,
  author = {Favati, P. and Lotti, G. and Romani, F.},
  title = {Theoretical and Practical Efficiency Measures for Symmetric Interpolatory
        Quadrature Fromulas},
  journal = {BIT Numerical Mathematics},
  year = {1994},
  volume = {34},
  pages = {546--557},
  number = {4}
}

@ARTICLE{Fer89,
  author = {Ferguson, Thomas S.},
  title = {Who Solved the Secretary Problem?},
  journal = {Statistical Science},
  year = {1989},
  volume = {4},
  pages = {pp. 282-289},
  number = {3},
  abstract = {In Martin Gardner's Mathematical Games column in the February 1960
        issue of Scientific American, there appeared a simple problem that
        has come to be known today as the Secretary Problem, or the Marriage
        Problem. It has since been taken up and developed by many eminent
        probabilists and statisticians and has been extended and generalized
        in many different directions so that now one can say that it constitutes
        a "field" within mathematics-probability-optimization. The object
        of this article is partly historical (to give a fresh view of the
        origins of the problem, touching upon Cayley and Kepler), partly
        review of the field (listing the subfields of recent interest), partly
        serious (to answer the question posed in the title), and partly entertainment.
        The contents of this paper were first given as the Allen T. Craig
        lecture at the University of Iowa, 1988.},
  copyright = {Copyright 1989 Institute of Mathematical Statistics},
  issn = {08834237},
  jstor_articletype = {research-article},
  jstor_formatteddate = {Aug., 1989},
  language = {English},
  owner = {tim},
  publisher = {Institute of Mathematical Statistics},
  timestamp = {2011.03.03},
  url = {http://www.jstor.org/stable/2245639}
}

@inproceedings{Fic08,
 author = {Ficici, Sevan G. and Pfeffer, Avi},
 title = {Modeling How Humans Reason About Others with Partial Information},
 booktitle = {Proceedings of the 7th International Joint Conference on Autonomous Agents and Multiagent Systems},
 volume = {1},
 series = {AAMAS '08},
 year = {2008},
 isbn = {978-0-9817381-0-9},
 location = {Estoril, Portugal},
 pages = {315--322},
 numpages = {8},
 url = {http://dl.acm.org/citation.cfm?id=1402383.1402431},
 acmid = {1402431},
 publisher = {International Foundation for Autonomous Agents and Multiagent Systems},
 address = {Richland, SC},
 keywords = {human models, negotiation, reasoning, uncertainty},
} 

@ARTICLE{Fil10,
  author = {Filzmoser, M.},
  title = {Automated vs. Human Negotiation},
  journal = {International Journal of Artificial Intelligence},
  year = {2010},
  volume = {4},
  pages = {64--77},
  number = {S10},
  owner = {Mark},
  timestamp = {2013.02.02}
}

@INCOLLECTION{ANAC2011Fis,
  author = {Fishel, Radmila and Bercovitch, Maya and Gal, Ya'akov(Kobi)},
  title = {BRAM Agent},
  booktitle = {Complex Automated Negotiations: Theories, Models, and Software Competitions},
  publisher = {Springer Berlin Heidelberg},
  year = {2013},
  editor = {Ito, Takayuki and Zhang, Minjie and Robu, Valentin and Matsuo, Tokuro},
  volume = {435},
  series = {Studies in Computational Intelligence},
  pages = {213-216},
  doi = {10.1007/978-3-642-30737-9\_15},
  isbn = {978-3-642-30736-2},
  url = {http://dx.doi.org/10.1007/978-3-642-30737-9\_15}
}

@INCOLLECTION{ANAC2011Fisshort,
  author = {Fishel, Radmila and Bercovitch, Maya and Gal, Ya'akov(Kobi)},
  title = {BRAM Agent},
  booktitle = {Complex Automated Negotiations: Theories, Models, and Software Competitions},
  publisher = {Springer Berlin Heidelberg},
  year = {2013},
  pages = {213-216},
  doi = {10.1007/978-3-642-30737-9\_15},
  isbn = {978-3-642-30736-2},
  url = {http://dx.doi.org/10.1007/978-3-642-30737-9\_15}
}

@INPROCEEDINGS{For97,
  author = {Foresee, D. and Hagan, M.T.},
  title = {Gauss-Newton approximation to Bayesian learning},
  booktitle = {International Conference on Neural Networks},
  year = {1997},
  volume = {3},
  pages = {1930--1935},
  organization = {IEEE},
  owner = {---},
  timestamp = {2011.07.05}
}

@BOOK{Fox68,
  title = {Chebyshev polynomials in numerical analysis},
  publisher = {Oxford university press London},
  year = {1968},
  author = {Fox, L. and Parker, I.B.},
  volume = {29},
  owner = {---},
  timestamp = {2011.07.17}
}

@ARTICLE{Fre83,
  author = {Freeman, P.R.},
  title = {The Secretary Problem and Its Extensions: A Review},
  journal = {International Statistical Review / Revue Internationale de Statistique},
  year = {1983},
  volume = {51},
  pages = {pp. 189-206},
  number = {2},
  abstract = {The development of what has come to be known as the secretary problem
        is traced from its origins in the early 1960's. All published work
        to date on the problem and its extensions is reviewed. /// Ce r\'{e}sum\'{e}
        trace le d\'{e}veloppement d\'{e}s son origine pendant la premi\'{e}re
        p\'{e}riode des ann\'{e}es 60 de ce qu'on appelle le probl\'{e}me
        du secr\'{e}taire. Il passe en revue tous les travaux sur ce probl\`{e}me
        et ses extensions qui ont d\'{e}j\`{a} \'{e}t\'{e} publi\i'{e}s.},
  copyright = {Copyright 1983 International Statistical Institute (ISI)},
  issn = {03067734},
  jstor_articletype = {research-article},
  jstor_formatteddate = {Aug., 1983},
  language = {English},
  owner = {tim},
  publisher = {International Statistical Institute (ISI)},
  timestamp = {2011.03.03},
  url = {http://www.jstor.org/stable/1402748}
}

@INCOLLECTION{ANAC2011Frie,
  author = {Frieder, Asaf and Miller, Gal},
  title = {Value Model Agent: A Novel Preference Profiler for Negotiation with
        Agents},
  booktitle = {Complex Automated Negotiations: Theories, Models, and Software Competitions},
  publisher = {Springer Berlin Heidelberg},
  year = {2013},
  editor = {Ito, Takayuki and Zhang, Minjie and Robu, Valentin and Matsuo, Tokuro},
  volume = {435},
  series = {Studies in Computational Intelligence},
  pages = {199-203},
  doi = {10.1007/978-3-642-30737-9\_12},
  isbn = {978-3-642-30736-2},
  url = {http://dx.doi.org/10.1007/978-3-642-30737-9\_12}
}

@INCOLLECTION{ANAC2011Frieshort,
  author = {Frieder, Asaf and Miller, Gal},
  title = {Value Model Agent: A Novel Preference Profiler for Negotiation with
        Agents},
  booktitle = {Complex Automated Negotiations: Theories, Models, and Software Competitions},
  publisher = {Springer Berlin Heidelberg},
  year = {2013},
  pages = {199-203},
  doi = {10.1007/978-3-642-30737-9\_12},
  isbn = {978-3-642-30736-2},
  url = {http://dx.doi.org/10.1007/978-3-642-30737-9\_12}
}

@INPROCEEDINGS{ANAC2013AgentKF,
  author = {Fujita, Katsuhide},
  title = {Automated Negotiating Agent with Strategy Adaptation for Multi-times Negotiations},
  booktitle = {IEEE 6th International Conference on Service-Oriented Computing and Applications (SOCA)},
  year = {2013},
  pages = {333-337},
  abstract = {International Automated Negotiating Agents Competition (ANAC) was
        held in conjunction with International Joint Conference on Autonomous
        Agents and Multi-Agent Systems (AAMAS). This competition brings together
        researchers from the negotiation community and provides a unique
        benchmark for evaluating practical negotiation strategies in multi-issue
        domains. The previous competitions have provided the novel ideas
        in the field of autonomous agent design. Recently, the focus of the
        competition is interleaving learning with negotiation strategies.
        In this paper, we propose AgentKF which estimates the opponent's
        strategies based on the past negotiation sessions. Our agent tries
        to compromise to the estimated maximum utility of the opponent by
        the end of the negotiation. In addition, our agent can adjust the
        speed of compromising and search the pareto frontier using past negotiation
        sessions. Our agent won the 1st prize in the qualifying round of
        ANAC-2013.},
  doi = {10.1109/SOCA.2013.33},
  keywords = {Autonomous agents;Equations;Estimation;Indium tin oxide;Joints;Pareto
        optimization;Protocols;Automated Negotiating Agents Competition;Multi-agent
        System;Multi-issue Negotiation}
}

@InCollection{ANAC2011Kawpaper,
  author      = {Fujita, Katsuhide and Ito, Takayuki and Baarslag, Tim and Hindriks, Koen V. and Jonker, Catholijn M. and Kraus, Sarit and Lin, Raz},
  title       = {The Second Automated Negotiating Agents Competition ({ANAC} 2011)},
  booktitle   = {Complex Automated Negotiations: Theories, Models, and Software Competitions},
  publisher   = {Springer Berlin Heidelberg},
  year        = {2013},
  editor      = {Ito, Takayuki and Zhang, Minjie and Robu, Valentin and Matsuo, Tokuro},
  volume      = {435},
  series      = {Studies in Computational Intelligence},
  pages       = {183-197},
  abstract    = {In May 2011, we organized the Second International Automated Negotiating
        Agents Competition (ANAC2011) in conjunction with AAMAS 2011. ANAC
        is an international competition that challenges researchers to develop
        a successful automated negotiator for scenarios where there is incomplete
        information about the opponent. One of the goals of this competition
        is to help steer the research in the area of bilateral multi-issue
        negotiations, and to encourage the design of generic negotiating
        agents that are able to operate in a variety of scenarios. Eighteen
        teams from seven different institutes competed in ANAC2011. This
        chapter describes the participating agents and the setup of the tournament,
        including the different negotiation scenarios that were used in the
        competition. We report on the results of the qualifying and final
        round of the tournament.},
  affiliation = {School of Engineering, The University of Tokyo, Tokyo, Japan},
  isbn        = {978-3-642-30736-2},
  keyword     = {Engineering},
  pdf         = {http://dx.doi.org/10.1007/978-3-642-30737-9_11},
  url         = {http://dx.doi.org/10.1007/978-3-642-30737-9\_11},
}

@INPROCEEDINGS{Fuj09,
  author = {Fujita, Katsuhide and Ito, Takayuki and Klein, Mark},
  title = {Approximately fair and secure protocols for multiple interdependent
        issues negotiation},
  booktitle = {Proceedings of The 8th International Conference on Autonomous Agents
        and Multiagent Systems},
        volume={2},
  year = {2009},
  series = {AAMAS '09},
  pages = {1287--1288},
  address = {Richland, SC},
  publisher = {International Foundation for Autonomous Agents and Multiagent Systems},
  acmid = {1558255},
  isbn = {978-0-9817381-7-8},
  keywords = {multi-issue negotiation, non-linear utility function},
  location = {Budapest, Hungary},
  numpages = {2},
  url = {http://dl.acm.org/citation.cfm?id=1558109.1558255}
}

@InCollection{Gal15,
  author    = {(Ya'akov) Gal, Kobi and Ilany, Litan},
  title     = {The Fourth Automated Negotiation Competition},
  booktitle = {Next Frontier in Agent-based Complex Automated Negotiation},
  publisher = {Springer Japan},
  year      = {2015},
  editor    = {Fujita, Katsuhide and Ito, Takayuki and Zhang, Minjie and Robu, Valentin},
  volume    = {596},
  series    = {Studies in Computational Intelligence},
  pages     = {129-136},
  doi       = {10.1007/978-4-431-55525-4_8},
  isbn      = {978-4-431-55524-7},
  keywords  = {Automated negotiation competition; Multi-issue negotiation},
  language  = {English},
  url       = {http://dx.doi.org/10.1007/978-4-431-55525-4_8},
}


@INPROCEEDINGS{Ful05,
  author = {Karen K. Fullam and Tomas B. Klos and Guillaume Muller and Jordi
        Sabater and Andreas Schlosser and K. Suzanne Barber and Jeffrey S.
        Rosenschein and Laurent Vercouter and Marco Voss},
  title = {A specification of the agent reputation and trust (art) testbed:
        experimentation and competition for trust in agent societies},
  booktitle = {The 4th International Joint Conference on Autonomous Agents and MultiAgent
        Systems (AAMAS)},
  year = {2005},
  pages = {512--518},
  publisher = {ACM Press},
  owner = {tim},
  timestamp = {2010.08.03}
}

@incollection{Fur00,
 author = {F\"{u}rnkranz, Johannes},
 title = {Machine Learning in Games: A Survey},
 booktitle = {Machines That Learn to Play Games},
 editor = {F\"{u}rnkranz, Johannes and Kubat, Miroslav},
 year = {2001},
 isbn = {1-59033-021-8},
 pages = {11--59},
 numpages = {49},
 url = {http://dl.acm.org/citation.cfm?id=644391.644393},
 acmid = {644393},
 publisher = {Nova Science Publishers, Inc.},
 address = {Commack, NY, USA},
} 


@INPROCEEDINGS{Gal05colored,
  author = {Gal, Ya'akov and Grosz, Barbara J. and Kraus, Sarit and Pfeffer, Avi and Shieber, Stuart},
  title = {Colored trails: a formalism for investigating decision-making in     strategic environments},
  booktitle = {Proceedings of the 2005 IJCAI workshop on reasoning, representation,     and learning in computer games},
  year = {2005},
  pages = {25--30}
}

@article{Gal11,
 author = {Gal, Ya'akov and Kraus, Sarit and Gelfand, Michele and Khashan, Hilal and Salmon, Elizabeth},
 title = {An Adaptive Agent for Negotiating with People in Different Cultures},
 journal = {ACM Transactions on Intelligent Systems and Technology},
 issue_date = {October 2011},
 volume = {3},
 number = {1},
 month = {Oct},
 year = {2011},
 issn = {2157-6904},
 pages = {8:1--8:24},
 articleno = {8},
 numpages = {24},
 url = {http://doi.acm.org/10.1145/2036264.2036272},
 doi = {10.1145/2036264.2036272},
 acmid = {2036272},
 publisher = {ACM},
 address = {New York, NY, USA},
 keywords = {Human-agent decision making, cultural modeling},
}

@article{Gal10,
title={Agent Decision-Making in Open Mixed Networks},
author="Y. Gal and B. Grosz and  S. Kraus and  A.  Pfeffer and  S. Shieber",
journal = "Artificial Intelligence",
volume="174",
number="18",
pages="1460--1480",
year = "2010",
DOI="doi:10.1016/j.artint.2010.09.002"
}

@INPROCEEDINGS{ANAC2010vanGExt,
  author = {Niels van Galen Last},
  title = {{Agent Smith}: Opponent model estimation in bilateral multi-issue negotiation},
  booktitle = {New Trends in Agent-based Complex Automated Negotiations},
        series={Studies in Computational Intelligence},
  year = {2012},
  editor = {Takayuki Ito and Minjie Zhang and Valentin Robu and Shaheen Fatima
        and Tokuro Matsuo},
  pages = {167-174},
  address = {Berlin, Heidelberg},
  publisher = {Springer-Verlag},
  isbn = {978-3-642-24695-1},
  owner = {tim}
}

@ARTICLE{ANAC2010vanG,
  author = {Niels van Galen Last},
  title = {Agent Smith: Opponent model estimation in bilateral multi-issue negotiation},
  journal = {This volume},
  year = {2012},
  pages = {167-174}
}

@INPROCEEDINGS{ANAC2010vanGExtshort,
  author = {Niels van Galen Last},
  title = {Agent Smith: Opponent model estimation in bilateral multi-issue negotiation},
  booktitle = {New Trends in Agent-based Complex Automated Negotiations},
  year = {2012},
  pages = {167-174},
  address = {Berlin, Heidelberg},
  publisher = {Springer-Verlag},
  isbn = {978-3-642-24695-1},
  owner = {tim}
}

@INPROCEEDINGS{Gan11,
  author = {Sam Ganzfried and Tuomas Sandholm},
  title = {Game Theory-Based Opponent Modeling in Large Imperfect-Information
        Games},
  booktitle = {The Tenth International Conference on Autonomous Agents and Multiagent
        Systems},
  year = {2011},
  editor = {Liz Sonenberg and Peter Stone and Kagan Tumer and Pinar Yolum},
  volume = {2},
  pages = {533--540},
  publisher = {IFAAMAS},
  owner = {Mark},
  timestamp = {2013.02.08}
}

@INBOOK{Gao10,
  pages = {3523-3528},
  title = {Research on the decision-making of multi-issue/attribute negotiation
        based on agent technology and the Genetic Algorithm},
  publisher = {IEEE},
  year = {2010},
  author = {Gao, Taiguang and Chen, Peiyou},
  booktitle = {Chinese Control and Decision Conference CCDC 2010},
  owner = {Mark},
  timestamp = {2013.02.08}
}

@ARTICLE{Gat08,
  author = {Gatti, N. and Di Giunta, F. and Marino, S.},
  title = {Alternating-offers bargaining with one-sided uncertain deadlines:
        an efficient algorithm},
  journal = {Artificial Intelligence},
  year = {2008},
  volume = {172},
  pages = {1119--1157},
  number = {8-9},
  owner = {Mark},
  publisher = {Elsevier},
  timestamp = {2012.01.07}
}

@BOOK{Geh98,
  title = {Management of Technology and Operations},
  publisher = {Wiley},
  year = {1998},
  author = {Gehani, R.R.},
  isbn = {9780471179061},
  lccn = {97053199},
  url = {http://books.google.nl/books?id=dT8BL1D9SEsC}
}

@MISC{Gei07,
  author = {Geipel, Markus M. and Weiss, Gerhard},
  title = {A Generic Framework for Argumentation-Based Negotiation},
  year = {2007},
  pages = {209-223},
  publisher = {Springer},
  volume = {4676}
}

@techreport{Ger00,
 author = {Enrico H. Gerding and David D.B. Bragt and Johannes A. La Poutr\'{e}},
 title = {Scientific approaches and techniques for negotiation: a game theoretic and artificial intelligence perspective},
 year = {2000},
 source = {http://www.ncstrl.org:8900/ncstrl/servlet/search?formname=detail\&id=oai%3Ancstrlh%3Aercim_cwi%3Aercim.cwi%2F%2FSEN-R0005},
 publisher = {CWI (Centre for Mathematics and Computer Science)},
 institution = {CWI (Centre for Mathematics and Computer Science)},
 address = {Amsterdam, The Netherlands},
}

@PHDTHESIS{GhoPhD,
  author = {Ghorbani, Amineh},
  title = {Structuring Socio-technical Complexity},
  year = {2013}
}
        
@ARTICLE{God93,
  author = {Gode, Dhananjay K. and Sunder, Shyam},
  title = {Allocative Efficiency in Markets with Zero Intelligence {(ZI)} Traders:
        Market as a Partial Substitute for Individual Rationality},
  journal = {Journal of Political Economy},
  year = {1993},
  volume = {101},
        ISSN = {00223808},
        publisher = {The University of Chicago Press},
  pages = {119-137},
  number = {1}
}

@BOOK{Goldberg1989,
  title = {Genetic algorithms in search, optimization, and machine learning},
  publisher = {Addison-Wesley Professional},
  year = {1989},
  author = {Goldberg, D.E.},
  owner = {---},
  timestamp = {2011.06.05}
}

@ARTICLE{Gre01,
  author = {Amy Greenwald and Peter Stone},
  title = {Autonomous Bidding Agents in the Trading Agent Competition},
  journal = {IEEE Internet Computing},
  year = {2001},
  volume = {5},
  pages = {52--60},
  number = {2},
  timestamp = {2010.06.03}
}

@INCOLLECTION{Guo03,
  author = {Guo, Y. and M{\"u}ller, J. and Weinhardt, C.},
  title = {Learning User Preferences for Multi-attribute Negotiation: An Evolutionary
        Approach},
  booktitle = {Multi-Agent Systems and Applications III},
  publisher = {Springer Berlin Heidelberg},
  year = {2003},
  volume = {2691},
  series = {Lecture Notes in Computer Science},
  pages = {303-313},
  doi = {10.1007/3-540-45023-8\_29},
  isbn = {978-3-540-40450-7},
  language = {English},
  owner = {Mark},
  timestamp = {2013.02.12},
  url = {http://dx.doi.org/10.1007/3-540-45023-8\_29}
}

@INCOLLECTION{Gut98,
  author = {Guttman, Robert H. and Maes, Pattie},
  title = {Agent-Mediated Integrative Negotiation for Retail Electronic Commerce},
  booktitle = {Agent Mediated Electronic Commerce},
  publisher = {Springer Berlin Heidelberg},
  year = {1999},
  editor = {Noriega, Pablo and Sierra, Carles},
  volume = {1571},
  series = {Lecture Notes in Computer Science},
  pages = {70-90},
  doi = {10.1007/3-540-48835-9\_5},
  isbn = {978-3-540-65955-6},
  language = {English},
  url = {http://dx.doi.org/10.1007/3-540-48835-9\_5}
}

@INPROCEEDINGS{Gwa01,
  author = {Gwak, Jeonghwan and Sim, Kwang Mong},
  title = {Bayesian learning based negotiation agents for supporting negotiation
        with incomplete information},
  booktitle = {Proceedings of the International MultiConference of Engineers and
        Computer Scientists},
          pages={163--168},
  year = {2011},
  volume = {1},
  owner = {Mark},
  timestamp = {2013.06.01}
}

@ARTICLE{Had03,
  author = {Ha, Vu and Haddawy, Peter},
  title = {Similarity of Personal Preferences: Theoretical Foundations and Empirical
        Analysis},
  journal = {Artificial Intelligence},
  year = {2003},
  volume = {146},
  pages = {149-173},
  number = {2}
}

@INPROCEEDINGS{Hab12,
  author = {Valeriia Haberland and Simon Miles and Michael Luck},
  title = {Adaptive Negotiation for Resource Intensive Tasks in Grids},
  booktitle = {STAIRS},
  year = {2012},
  pages = {125-136},
  ee = {http://dx.doi.org/10.3233/978-1-61499-096-3-125},
  owner = {Mark},
  timestamp = {2013.05.28}
}

@TECHREPORT{Hal02,
  author = {David Hales},
  title = {Neg-o-net - a negotiation simulation test-bed},
  institution = {CPM},
  year = {2002},
  number = {CPM-02-109},
  month = {Apr}
}


@MISC{Har08,
  author = {Harrenstein, Paul and Mahr, Tamas and de Weerdt, Mathijs M.},
  title = {A Qualitative Vickrey Auction},
  year = {2008},
  pages = {289-301},
  publisher = {University of Liverpool}
}

@MISC{Har09,
  author = {Harrenstein, Paul and de Weerdt, Mathijs M. and Conitzer, Vincent},
  title = {A Qualitative Vickrey Auction},
  year = {2009},
  pages = {197-206},
  publisher = {ACM Press}
}

@BOOK{Hay94,
  title = {Neural networks: a comprehensive foundation},
  publisher = {Prentice Hall PTR Upper Saddle River, NJ, USA},
  year = {1994},
      day = {16},
    edition = {2},
    isbn = {0132733501},
  author = {Haykin, Simon},
  owner = {---},
  timestamp = {2011.06.18}
}

@ARTICLE{He03,
  author = {Minghua He and Jennings, Nicholas R. and {Ho-fung} Leung},
  title = {On agent-mediated electronic commerce},
  journal = {IEEE Transactions on Knowledge and Data Engineering},
  year = {2003},
  volume = {15},
  pages = {985-1003},
  number = {4},
  doi = {10.1109/TKDE.2003.1209014},
  issn = {1041-4347},
  keywords = {electronic commerce;multi-agent systems;software agents;agent-mediated
        electronic commerce;business-to-business aspects;business-to-consumer
        aspects;buyer coalition formation;consumer buying behavior;intelligent
        agents;merchant brokering;need identification;product brokering;Application
        software;Automation;Business;Electronic commerce;Helium;Impedance;Intelligent
        agent;Law;Legal factors;Software quality}
}

@INCOLLECTION{Hen03,
  author = {Henderson, Peter and Crouch, Stephen and Walters, Robert John and Ni, Qinglai},
  title = {Comparison of Some Negotiation Algorithms Using a Tournament-Based Approach},
  booktitle = {Agent Technologies, Infrastructures, Tools, and Applications for E-Services},
  publisher = {Springer Berlin Heidelberg},
  year = {2003},
  editor = {Carbonell, Jaime G. and Siekmann, J\"{o}rg and Kowalczyk, Ryszard
        and M\"{u}ller, J\"{o}rg P. and Tianfield, Huaglory and Unland, Rainer},
  volume = {2592},
  series = {Lecture Notes in Computer Science},
  pages = {137-150},
  doi = {10.1007/3-540-36559-1\_12},
  isbn = {978-3-540-00742-5},
  language = {English},
  owner = {Mark},
  timestamp = {2013.02.12},
  url = {http://dx.doi.org/10.1007/3-540-36559-1\_12}
}

@mastersthesis{hendrikx2012evaluating,
  title={Evaluating the Quality of Opponent Models in Automated Bilateral Negotiations},
  author={Hendrikx, M.J.C.},
  year={2012},
  school={Delft University of Technology}
}

@INPROCEEDINGS{Her05,
  author = {Jaap van den Herik and Jeroen Donkers and Pieter H.M. Spronck},
  title = {Opponent Modelling and Commercial Games},
  booktitle = {Proceedings of the IEEE 2005 Symposium on Computational Intelligence
        and Games},
  year = {2005},
  editor = {Graham Kendall and Simon Lucas},
  pages = {15--25},
  owner = {Mark},
  timestamp = {2013.02.08}
}

@INCOLLECTION{Hin07,
  author = {Hindriks, Koen V. and Jonker, Catholijn M. and Tykhonov, Dmytro},
  title = {Analysis of Negotiation Dynamics},
  booktitle = {Cooperative Information Agents XI},
  publisher = {Springer Berlin Heidelberg},
  year = {2007},
  editor = {Klusch, Matthias and Hindriks, Koen V. and Papazoglou, Mike P. and
        Sterling, Leon},
  volume = {4676},
  series = {Lecture Notes in Computer Science},
  pages = {27-35},
  doi = {10.1007/978-3-540-75119-9\_3},
  isbn = {978-3-540-75118-2},
  url = {http://dx.doi.org/10.1007/978-3-540-75119-9\_3}
}

@ARTICLE{Hin11,
  author = {Hindriks, Koen V. and Jonker, Catholijn M. and Tykhonov, Dmytro},
  title = {Let's dans! {An} analytic framework of negotiation dynamics and strategies},
  journal = {Web Intelligence and Agent Systems},
  year = {2011},
  volume = {9},
  pages = {319--335},
   issn = {1570-1263},
    doi = {10.3233/WIA-2011-0221},
  number = {4},
   month = {Dec},
  owner = {---},
  publisher = {IOS Press},
 address = {Amsterdam, The Netherlands, The Netherlands},
  timestamp = {2011.08.19}
}

@INPROCEEDINGS{Hin09Benefits,
  author = {Hindriks, Koen V. and Jonker, Catholijn M. and Tykhonov, Dmytro},
  title = {The Benefits of Opponent Models in Negotiation},
  booktitle = {Proceedings of the 2009 IEEE/WIC/ACM International Joint Conference on Web Intelligence and Intelligent Agent Technology},
  year = {2009},
  month={Sep}, 
  volume = {2},
  doi={10.1109/WI-IAT.2009.192},
  pages = {439--444},
  organization = {IEEE Computer Society},
  owner = {---},
  timestamp = {2011.05.22}
}

@INPROCEEDINGS{Hin09Opponent,
  author = {Hindriks, Koen V. and Jonker, Catholijn M. and Tykhonov, Dmytro},
  title = {Using opponent models for efficient negotiation},
  booktitle = {Proceedings of The 8th International Conference on Autonomous Agents
        and Multiagent Systems},
  year = {2009},
  volume = {2},
  series = {AAMAS '09},
  pages = {1243--1244},
  publisher = {International Foundation for Autonomous Agents and Multiagent Systems},
  location = {Budapest, Hungary},
  numpages = {2},
  owner = {---},
  timestamp = {2011.08.19}
}

@MISC{Hin09usi,
  author = {Hindriks, Koen V. and Jonker, Catholijn M. and Tykhonov, Dmytro},
  title = {Using Opponent Models for Efficient Negotiation (Extended Abstract)},
  year = {2009}
}

@INPROCEEDINGS{Hin09Genius,
  author = {Hindriks, Koen V. and Jonker, Catholijn M. and Kraus, Sarit and Lin,
        Raz and Tykhonov, Dmytro},
  title = {Genius: negotiation environment for heterogeneous agents},
  booktitle = {Proceedings of The 8th International Conference on Autonomous Agents
        and Multiagent Systems},
        volume = {2},
  year = {2009},
  series = {AAMAS '09},
  pages = {1397--1398},
  address = {Richland, SC},
  publisher = {International Foundation for Autonomous Agents and Multiagent Systems},
  acmid = {1558313},
  isbn = {978-0-9817381-7-8},
  keywords = {automated multi-issue negotiation, negotiation, negotiation strategy,
        testbed},
  location = {Budapest, Hungary},
  numpages = {2},
  url = {http://dl.acm.org/citation.cfm?id=1558109.1558313}
}

@INPROCEEDINGS{Hin07Negotiation,
  author = {Hindriks, Koen V. and Jonker, Catholijn M. and Tykhonov, Dmytro},
  title = {Negotiation Dynamics: Analysis, Concession Tactics, and Outcomes},
  booktitle = {Proceedings of the 2007 IEEE/WIC/ACM International Conference on
        Intelligent Agent Technology},
  year = {2007},
  series = {IAT '07},
  pages = {427--433},
  address = {Washington, DC, USA},
  publisher = {IEEE Computer Society},
  acmid = {1331698},
  doi = {10.1109/IAT.2007.73},
  isbn = {0-7695-3027-3},
  numpages = {7},
  url = {http://dx.doi.org/10.1109/IAT.2007.73}
}

@INCOLLECTION{Hin08ope,
  author = {Hindriks, Koen V. and Jonker, Catholijn M. and Tykhonov, Dmytro},
  title = {Towards an Open Negotiation Architecture for Heterogeneous Agents},
  booktitle = {Cooperative Information Agents XII},
  publisher = {Springer Berlin Heidelberg},
  year = {2008},
  editor = {Klusch, Matthias and Pechoucek, Michal and Polleres, Axel},
  volume = {5180},
  series = {Lecture Notes in Computer Science},
  pages = {264-279},
  doi = {10.1007/978-3-540-85834-8\_21},
  isbn = {978-3-540-85833-1},
  url = {http://dx.doi.org/10.1007/978-3-540-85834-8\_21}
}

@INPROCEEDINGS{Hin08Human,
  author = {Hindriks, Koen V. and Jonker, Catholijn M.},
  title = {Creating human-machine synergy in negotiation support systems: towards
        the pocket negotiator},
  booktitle = {Proceedings of the 1st International Working Conference on Human
        Factors and Computational Models in Negotiation},
  year = {2009},
  series = {HuCom '08},
  pages = {47--54},
  address = {New York, NY, USA},
  publisher = {ACM},
  acmid = {1609176},
  doi = {10.1145/1609170.1609176},
  isbn = {978-90-813811-1-6},
  keywords = {artificial intelligence, human computer interaction, negotiation,
        situated cognitive engineering},
  location = {Delft, The Netherlands},
  numpages = {8},
  url = {http://doi.acm.org/10.1145/1609170.1609176}
}

@INCOLLECTION{Hin08qua,
  author = {Hindriks, Koen V. and Tykhonov, Dmytro},
  title = {Towards a Quality Assessment Method for Learning Preference Profiles
        in Negotiation},
  booktitle = {Agent-Mediated Electronic Commerce and Trading Agent Design and Analysis},
  publisher = {Springer Berlin Heidelberg},
  year = {2010},
  editor = {Wolfgang Ketter and Johannes A. La Poutr\'{e} and Norman Sadeh and Onn Shehory and William Walsh},
  volume = {44},
  series = {Lecture Notes in Business Information Processing},
  pages = {46-59},
  doi = {10.1007/978-3-642-15237-5\_4},
  isbn = {978-3-642-15236-8},
  url = {http://dx.doi.org/10.1007/978-3-642-15237-5\_4}
}

@INCOLLECTION{Hin08quashort,
  author = {Hindriks, Koen V. and Tykhonov, Dmytro},
  title = {Towards a Quality Assessment Method for Learning Preference Profiles
        in Negotiation},
  booktitle = {Agent-Mediated Electronic Commerce and Trading Agent Design and Analysis},
  publisher = {Springer Berlin Heidelberg},
  year = {2010},
  isbn = {978-3-642-15236-8},
  owner = {Mark},
  timestamp = {2013.04.20}
}

@INPROCEEDINGS{Hin08opp,
  author = {Hindriks, Koen V. and Tykhonov, Dmytro},
  title = {Opponent modelling in Automated Multi-issue Negotiation Using Bayesian
        Learning},
  booktitle = {Proceedings of the 7th international joint conference on Autonomous
        agents and multiagent systems},
        volume = {1},
  year = {2008},
  series = {AAMAS '08},
  pages = {331--338},
  address = {Richland, SC},
  publisher = {International Foundation for Autonomous Agents and Multiagent Systems},
  acmid = {1402433},
  isbn = {978-0-9817381-0-9},
  keywords = {Bayesian learning, automated multi-issue negotiation, opponent modelling,
        preference profiles},
  location = {Estoril, Portugal},
  numpages = {8},
  url = {http://dl.acm.org/citation.cfm?id=1402383.1402433}
}

@INPROCEEDINGS{Hin08oppshort,
  author = {Hindriks, Koen V. and Tykhonov, Dmytro},
  title = {Opponent modelling in Automated Multi-issue Negotiation Using Bayesian
        Learning},
  booktitle = {Proceedings of the 7th international joint conference on Autonomous
        agents and multiagent systems},
        volume = {1},
  year = {2008},
  acmid = {1402433},
  isbn = {978-0-9817381-0-9},
  location = {Estoril, Portugal},
  numpages = {8},
  owner = {Mark},
  timestamp = {2013.04.20}
}

@MISC{Hin08qua2,
  author = {Hindriks, Koen V. and Tykhonov, Dmytro},
  title = {Towards a Quality Assessment Method for Learning Preference Profiles
        in Negotiation},
  year = {2008},
  pages = {64-71}
}

@MISC{Hin08HuCom,
  author = {Hindriks, Koen V. and Tykhonov, Dmytro and de Weerdt, Mathijs},
  title = {Approximating an Auction Mechanism by Multi-Issue Negotiation},
  month = {Dec},
  year = {2008},
  pages = {33-38}
}

@MISC{Hin09app,
  author = {Hindriks, Koen V. and Tykhonov, Dmytro and de Weerdt, Mathijs M.},
  title = {Approximating the Qualitative Vickrey Auction by a Negotiation Protocol},
  year = {2009}
}

@BOOK{hodgson1996thinking,
  title = {Thinking on your feet in negotiations},
  publisher = {Pitman Great Britain, UK},
  year = {1996},
  author = {Hodgson, J. and Institute of Management (Great Britain)}
}

@INPROCEEDINGS{Hou04,
  author = {Chongming Hou},
  title = {Predicting agents tactics in automated negotiation},
  booktitle = {Proceedings of the IEEE/WIC/ACM International Conference on Intelligent Agent Technology},
  year = {2004},
  doi={10.1109/IAT.2004.1342934},
  month={Sep}, 
  pages = {127--133},
  publisher = {IEEE Computer Society},
  owner = {---},
  timestamp = {2011.07.03}
}

@ARTICLE{Hua08,
  author = {Huang, Shiu-li and Lin, Fu-ren},
  title = {Using temporal-difference learning for multi-agent bargaining},
  journal = {Electron. Commer. Rec. Appl.},
  year = {2008},
  volume = {7},
  pages = {432--442},
  month = {Dec},
  acmid = {1466114},
  address = {Amsterdam, The Netherlands, The Netherlands},
  issn = {1567-4223},
  issue = {4},
  numpages = {11},
  owner = {Mark},
  publisher = {Elsevier Science Publishers B. V.},
  timestamp = {2013.02.08}
}

@INPROCEEDINGS{Lit13,
  author = {Litan Ilany and Ya'akov Gal},
  title = {Algorithm Selection in Bilateral Negotiation},
  booktitle = {Proceedings of The Sixth International Workshop on Agent-based Complex
        Automated Negotiations (ACAN 2013)},
  year = {2013},
  owner = {Mark},
  timestamp = {2013.06.21}
}

@Article{Lit15,
  author    = {Ilany, Litan and Gal, Ya'akov},
  title     = {Algorithm selection in bilateral negotiation},
  journal   = {Autonomous Agents and Multi-Agent Systems},
  year      = {2015},
  pages     = {1-27},
  doi       = {10.1007/s10458-015-9302-8},
  issn      = {1387-2532},
  keywords  = {Multi-agent negotiation under incomplete information; Empirical methods; GENIUS framework; Algorithm selection},
  language  = {English},
  publisher = {Springer US},
  url       = {http://dx.doi.org/10.1007/s10458-015-9302-8},
}

@INPROCEEDINGS{Ito07,
  author = {Ito, Takayuki and Hattori, Hiromitsu and Klein, Mark},
  title = {Multi-issue negotiation protocol for agents: exploring nonlinear     utility spaces},
  booktitle = {Proceedings of the 20th international joint conference on artifical
        intelligence},
  year = {2007},
  series = {IJCAI'07},
  pages = {1347--1352},
  address = {San Francisco, CA, USA},
  publisher = {Morgan Kaufmann Publishers Inc.},
  acmid = {1625493},
  location = {Hyderabad, India},
  numpages = {6},
  url = {http://dl.acm.org/citation.cfm?id=1625275.1625493}
}

@ARTICLE{Ito08,
  author = {Ito, Takayuki and Klein, Mark and Hattori, Hiromitsu},
  title = {A multi-issue negotiation protocol among agents with nonlinear utility
        functions},
  journal = {Multiagent and Grid Systems},
  year = {2008},
  volume = {4},
  pages = {67--83},
  number = {1},
  month = {Jan},
  acmid = {1378678},
  address = {Amsterdam, The Netherlands, The Netherlands},
  issn = {1574-1702},
  keywords = {Multi-issue negotiation, multi-agent systems, non-linear utility},
  numpages = {17},
  publisher = {IOS Press},
  url = {http://dl.acm.org/citation.cfm?id=1378675.1378678}
}

@ARTICLE{Ito08short,
  author = {Ito, Takayuki and Klein, Mark and Hattori, Hiromitsu},
  title = {A multi-issue negotiation protocol among agents with nonlinear utility
        functions},
  journal = {Multiagent and Grid Systems},
  year = {2008},
  volume = {4},
  pages = {67--83},
  number = {1},
  month = {Jan},
  acmid = {1378678},
  address = {Amsterdam, The Netherlands, The Netherlands},
  issn = {1574-1702},
  issue_date = {January 2008},
  keywords = {Multi-issue negotiation, multi-agent systems, non-linear utility},
  numpages = {17},
  publisher = {IOS Press}
}

@ARTICLE{Jaz11Softcomputing,
  author = {Jazayeriy, Hamid and Azmi-Murad, Masrah and Sulaiman, Md. Nasir and Udzir, Nur Izura},
  title = {A review on soft computing techniques in automated negotiation},
  journal = {Scientific Research and Essays},
  year = {2011},
  volume = {6},
  pages = {5100--5106},
  number = {24},
  owner = {Mark},
  timestamp = {2012.01.11}
}

@ARTICLE{Jaz11Preferences,
  author = {Jazayeriy, Hamid AND Azmi-Murad, Masrah AND Sulaiman, Nasir AND Izura
        Udizir, Nur},
  title = {The Learning of an Opponent's Approximate Preferences in Bilateral
        Automated Negotiation},
  journal = {Journal of theoretical and applied electronic commerce research},
  year = {2011},
  volume = {6},
  pages = {65--84},
  number = {3},
  month = {Dec},
  issn = {0718-1876},
  owner = {Mark},
  publisher = {SciELO Chile},
  timestamp = {2012.04.16}
}

@ARTICLE{Jen01,
  author = {Jennings, Nicholas R. and Faratin, Peyman and Lomuscio, Alessio R. and Parsons, Simon and Wooldridge, Michael J. and Sierra, Carles},
  title = {Automated Negotiation: Prospects, Methods and Challenges},
  journal = {Group Decision and Negotiation},
  year = {2001},
  volume = {10},
  pages = {199--215},
  number = {2},
  issn = {0926-2644},
  language = {English},
  owner = {tim},
  publisher = {Kluwer Academic Publishers},
  timestamp = {2010.04.15}
}

@INPROCEEDINGS{Jen92,
  author = {Nicholas R. Jennings and E.H. Mamdani},
  title = {Using Joint Responsibility to Coordinate Collaborative Problem Solving in Dynamic Environments},
  booktitle = {10th National Conf. on Artificial Intelligence (AAAI-92)},
  year = {1992},
  pages = {269--275},
  abstract = {Joint responsibility is a new meta-level description of how cooperating
        agents should behave when engaged in collaborative problem solving.
        It is dependent of any specific planning or concensus forming mechanism,
        but can be mapped down to such a level. An application of the framework
        to the real world problem of electricity transportation management
        is given and its implementation is discussed. A comparative analysis
        of responsibility and two other group organisational structures,
        selfish problem solvers and communities in which collaborative behaviour
        emerges from interactions, is undertaken. The aim being to evaluatetheir
        relative performance characteristics in dynamic and unpredictable
        environments in which decisions are taken using partial, imprecise
        views of the system.},
  url = {http://eprints.soton.ac.uk/252131/}
}

@book{Jenk77,
  title={Optimal Data Classification For Choropleth Maps},
  author={Jenks, George F. and University of Kansas, Dept. of Geography},
  series={Occasional paper},
  url={http://books.google.nl/books?id=HvAENQAACAAJ},
  year={1977},
  publisher={University of Kansas}
}

@book{Jol05,
title = {Principal Component Analysis},
author = {Jolliffe, Ian},
publisher = {John Wiley \& Sons, Ltd},
isbn = {9780470013199},
url = {http://dx.doi.org/10.1002/0470013192.bsa501},
doi = {10.1002/0470013192.bsa501},
keywords = {dimension reduction, factor analysis, multivariate analysis, variance maximization},
booktitle = {Encyclopedia of Statistics in Behavioral Science},
year = {2005},
abstract = {When large multivariate datasets are analyzed, it is often desirable to reduce their dimensionality. Principal component analysis is one technique for doing this. It replaces the p original variables by a smaller number, q, of derived variables, the principal components, which are linear combinations of the original variables. Often, it is possible to retain most of the variability in the original variables with q very much smaller than p. Despite its apparent simplicity, principal component analysis has a number of subtleties, and it has many uses and extensions. A number of choices associated with the technique are briefly discussed, namely, covariance or correlation, how many components, and different normalization constraints, as well as confusion with factor analysis. Various uses and extensions are outlined.},
}


@ARTICLE{jones1996brief,
  author = {Jones, Michael C. and Marron, James S. and Sheather, Simon J.},
  title = {A Brief Survey of Bandwidth Selection for Density Estimation},
  journal = {Journal of the American Statistical Association},
  year = {1996},
  volume = {91},
  pages = {401--407},
  number = {433},
  doi = {10.1080/01621459.1996.10476701},
  eprint = {http://www.tandfonline.com/doi/pdf/10.1080/01621459.1996.10476701},
  timestamp = {2011.07.01},
  url = {http://www.tandfonline.com/doi/abs/10.1080/01621459.1996.10476701}
}

@INPROCEEDINGS{Sie12,
  author = {de Jonge, D. and Sierra, C.},
  title = {Automated Negotiation for Package Delivery},
  booktitle = {IEEE Sixth International Conference on Self-Adaptive and Self-Organizing Systems Workshops},
  year = {2012},
  pages = {83-88},
  doi = {10.1109/SASOW.2012.23},
  keywords = {algorithm theory;goods distribution;travelling salesman problems;tree
        searching;automated negotiation algorithm;package delivery company;profit;Automated
        Negotiation;Branch and Bound;Non-linear Utility;Package Delivery;Search}
}

@INPROCEEDINGS{Jon04,
  author = {Jonker, Catholijn M. and Robu, Valentin},
  title = {Automated Multi-Attribute Negotiation with Efficient Use of Incomplete
        Preference Information},
  booktitle = {Proceedings of the Third International Joint Conference on Autonomous
        Agents and Multiagent Systems},
        volume = {3},
  year = {2004},
  series = {AAMAS '04},
  pages = {1054--1061},
  address = {Washington, DC, USA},
  publisher = {IEEE Computer Society},
  acmid = {1018874},
  doi = {10.1109/AAMAS.2004.70},
  isbn = {1-58113-864-4},
  location = {New York, NY, USA},
  numpages = {8},
  url = {http://dx.doi.org/10.1109/AAMAS.2004.70}
}

@ARTICLE{Jon07,
  author = {Jonker, Catholijn M. and Robu, Valentin and Treur, Jan},
  title = {An agent architecture for multi-attribute negotiation using incomplete preference information},
  journal = {Autonomous Agents and Multi-Agent Systems},
  year = {2007},
  volume = {15},
  pages = {221-252},
  abstract = {(ABMP paper) A component-based generic agent architecture for multi-attribute
        (integrative) negotiation is introduced and its application is described
        in a prototype system for negotiation about cars, developed in cooperation
        with, among others, Dutch Telecom KPN. The approach can be characterized
        as cooperative one-to-one multi-criteria negotiation in which the
        privacy of both parties is protected as much as desired. We model
        a mechanism in which agents are able to use any amount of incomplete
        preference information revealed by the negotiation partner in order
        to improve the efficiency of the reached agreements. Moreover, we
        show that the outcome of such a negotiation can be further improved
        by incorporating a guessing heuristic, by which an agent uses the
        history of the opponent's bids to predict his preferences. Experimental
        evaluation shows that the combination of these two strategies leads
        to agreement points close to or on the Pareto-efficient frontier.
        The main original contribution of this paper is that it shows that
        it is possible for parties in a cooperative negotiation to reveal
        only a limited amount of preference information to each other, but
        still obtain significant joint gains in the outcome.},
  affiliation = {Delft University of Technology Faculty of Electrical Engineering,
        Mathematics and Computer Science Mekelweg 4 2628 CD Delft The Netherlands},
  issn = {1387-2532},
  issue = {2},
  keyword = {Computer Science},
  publisher = {Springer Netherlands},
  url = {http://dx.doi.org/10.1007/s10458-006-9009-y}
}

@INPROCEEDINGS{Jon01,
  author = {Catholijn M. Jonker and Jan Treur},
  title = {An Agent Architecture for Multi-Attribute Negotiation},
  booktitle = {Proceedings of IJCAI'01},
  year = {2001},
  pages = {1195-1201}
}

@ARTICLE{Jon07PN,
  author = {Jonker, Catholijn M.},
  title = {The pocket negotiator, synergy between man and machine},
  journal = {{NWO} Grant proposal},
  year = {2007},
  url = {http://ii.tudelft.nl/negotiation/images/2/25/Pocket\_negotiator.pdf}
}

@ARTICLE{Kael96,
  author = {Kaelbling, L.P. and Littman, M.L. and Moore, A.W.},
  title = {Reinforcement learning: A survey},
  journal = {Journal of Artificial Intelligence Research},
  year = {1996},
  volume = {4},
  pages = {237--285},
  owner = {Mark},
  timestamp = {2012.01.08}
}

@INCOLLECTION{Kam09,
  author = {Kamphorst, Bart and Wissen, Arlette and Dignum, Virginia},
  title = {Incorporating BDI Agents into Human-Agent Decision Making Research},
  booktitle = {Engineering Societies in the Agents World X},
  publisher = {Springer Berlin Heidelberg},
  year = {2009},
  editor = {Aldewereld, Huib and Dignum, Virginia and Picard, Gauthier},
  volume = {5881},
  series = {Lecture Notes in Computer Science},
  pages = {84-97},
  doi = {10.1007/978-3-642-10203-5\_8},
  isbn = {978-3-642-10202-8},
  url = {http://dx.doi.org/10.1007/978-3-642-10203-5\_8}
}

@INPROCEEDINGS{Kar04,
  author = {Karp, Alan H. and Wu, Ren and Chen, Kay-yut and Zhang, Alex},
  title = {A game tree strategy for automated negotiation},
  booktitle = {Proceedings of the 5th ACM conference on Electronic commerce},
  year = {2004},
  series = {EC '04},
  pages = {228--229},
  address = {New York, NY, USA},
  publisher = {ACM},
  acmid = {988807},
  doi = {10.1145/988772.988807},
  isbn = {1-58113-771-0},
  keywords = {automated negotiation},
  location = {New York, NY, USA},
  numpages = {2},
  url = {http://doi.acm.org/10.1145/988772.988807}
}

@INPROCEEDINGS{ANAC2010KawExt,
  author = {Shogo Kawaguchi and Katsuhide Fujita and Takayuki Ito},
  title = {Compromising Strategy based on Estimated Maximum Utility for Automated
        Negotiating Agents},
  booktitle = {New Trends in Agent-based Complex Automated Negotiations, Series
        of Studies in Computational Intelligence},
  year = {2012},
  editor = {Takayuki Ito and Minjie Zhang and Valentin Robu and Shaheen Fatima
        and Tokuro Matsuo},
  pages = {137-144},
  address = {Berlin, Heidelberg},
  publisher = {Springer-Verlag},
  isbn = {978-3-642-24695-1},
  owner = {tim},
  url = {http://link.springer.com/content/pdf/10.1007%2F978-3-642-24696-8_8}
}

@INCOLLECTION{Kaw12,
  author = {Kawaguchi, Shogo and Fujita, Katsuhide and Ito, Takayuki},
  title = {{AgentK}: Compromising Strategy based on Estimated Maximum Utility
        for Automated Negotiating Agents},
  booktitle = {New Trends in Agent-Based Complex Automated Negotiations},
  publisher = {Springer Berlin Heidelberg},
  year = {2012},
  editor = {Ito, Takayuki and Zhang, Minjie and Robu, Valentin and Fatima, Shaheen
        and Matsuo, Tokuro},
  volume = {383},
  series = {Studies in Computational Intelligence},
  pages = {137-144},
  doi = {10.1007/978-3-642-24696-8\_8},
  isbn = {978-3-642-24695-1},
  language = {English},
  owner = {Mark},
  timestamp = {2013.06.24},
  url = {http://dx.doi.org/10.1007/978-3-642-24696-8\_8}
}

@INCOLLECTION{ANAC2011Kaw,
  author = {Kawaguchi, Shogo and Fujita, Katsuhide and Ito, Takayuki},
  title = {{AgentK2}: Compromising Strategy Based on Estimated Maximum Utility
        for Automated Negotiating Agents},
  booktitle = {Complex Automated Negotiations: Theories, Models, and Software Competitions},
  publisher = {Springer Berlin Heidelberg},
  year = {2013},
  editor = {Ito, Takayuki and Zhang, Minjie and Robu, Valentin and Matsuo, Tokuro},
  volume = {435},
  series = {Studies in Computational Intelligence},
  pages = {235-241},
  doi = {10.1007/978-3-642-30737-9\_19},
  isbn = {978-3-642-30736-2},
  url = {http://dx.doi.org/10.1007/978-3-642-30737-9\_19}
}

@INCOLLECTION{ANAC2010KawExt2,
  author = {Kawaguchi, Shogo and Fujita, Katsuhide and Ito, Takayuki},
  title = {Compromising Strategy Based on Estimated Maximum Utility for Automated
        Negotiation Agents Competition ({ANAC}-10)},
  booktitle = {Modern Approaches in Applied Intelligence},
  publisher = {Springer Berlin Heidelberg},
  year = {2011},
  editor = {Mehrotra, Kishan G. and Mohan, Chilukuri K. and Oh, Jae C. and Varshney,
        Pramod K. and Ali, Moonis},
  volume = {6704},
  series = {Lecture Notes in Computer Science},
  pages = {501-510},
  doi = {10.1007/978-3-642-21827-9\_51},
  isbn = {978-3-642-21826-2},
  url = {http://dx.doi.org/10.1007/978-3-642-21827-9\_51}
}

@INCOLLECTION{ANAC2011Kawshort,
  author = {Kawaguchi, Shogo and Fujita, Katsuhide and Ito, Takayuki},
  title = {AgentK2: Compromising Strategy Based on Estimated Maximum Utility
        for Automated Negotiating Agents},
  booktitle = {Complex Automated Negotiations: Theories, Models, and Software Competitions},
  publisher = {Springer Berlin Heidelberg},
  year = {2013},
  pages = {235-241},
  doi = {10.1007/978-3-642-30737-9\_19},
  isbn = {978-3-642-30736-2},
  url = {http://dx.doi.org/10.1007/978-3-642-30737-9\_19}
}

@INCOLLECTION{ANAC2011Kawshorter,
  author = {Kawaguchi, Shogo and Fujita, Katsuhide and Ito, Takayuki},
  title = {{AgentK2}: Compromising Strategy Based on Estimated Maximum Utility
        for Automated Negotiating Agents},
  booktitle = {Complex Automated Negotiations: Theories, Models, and Software Competitions},
  publisher = {Springer Berlin Heidelberg},
  year = {2013},
  pages = {235-241},
  isbn = {978-3-642-30736-2},
  owner = {Mark},
  timestamp = {2013.04.20}
}

@ARTICLE{ANAC2010Kaw,
  author = {Shogo Kawaguchi and Katsuhide Fujita and Takayuki Ito},
  title = {Compromising Strategy based on Estimated Maximum Utility for Automated
        Negotiating Agents},
  journal = {This volume},
  year = {2012},
  pages = {137-144}
}

@BOOK{Kee76,
  title = {Decisions with Multiple Objectives},
  publisher = {Cambridge University Press},
  year = {1976},
  author = {Keeney, Ralph L. and Raiffa, Howard}
}

@article{Ker13,
title = "Concession-making in multi-attribute auctions and multi-bilateral negotiations: Theory and experiments",
journal = "Electronic Commerce Research and Applications",
volume = "12",
number = "3",
pages = "166-180",
year = "2013",
note = "Negotiation and E-Commerce",
issn = "1567-4223",
doi = "http://dx.doi.org/10.1016/j.elerap.2013.02.002",
url = "http://www.sciencedirect.com/science/article/pii/S1567422313000136",
author = "Gregory E. Kersten and Rustam M. Vahidov and Dmitry Gimon",
keywords = "Online auctions",
}

@ARTICLE{Ker07,
  author = {Kersten, Gregory E. and Lai, Hsiangchu},
  title = {Negotiation Support and E-negotiation Systems: An Overview},
  journal = {Group Decision and Negotiation},
  year = {2007},
  volume = {16},
  pages = {553-586},
  number = {6},
  doi = {10.1007/s10726-007-9095-5},
  issn = {0926-2644},
  keywords = {Negotiation support systems; Electronic negotiations; NSS research;
        NSS applications; ENS research; ENS applications; Negotiation software
        agents; Negotiation software assistants},
  language = {English},
  publisher = {Springer Netherlands},
  url = {http://dx.doi.org/10.1007/s10726-007-9095-5}
}

@ARTICLE{Ker99,
  author = {G.E. Kersten and S.J. Noronha},
  title = {{WWW}-based negotiation support: design, implementation, and use},
  journal = {Decision Support Systems},
  year = {1999},
  volume = {25},
  pages = {135-154},
  number = {2}
}

@ARTICLE{Ker97,
  author = {Kersten, G.E. and Noronha, S.J.},
  title = {Rational agents, contract curves, and inefficient compromises},
  journal = {Trans. Sys. Man Cyber. Part A},
  year = {1998},
  volume = {28},
  pages = {326--338},
  number = {3},
  month = {May},
  abstract = {Several studies of two-party negotiations have shown that negotiators
        more often than not reach inefficient compromises. We analyze the
        circumstances under which rational agents make inefficient compromises
        and refrain from improving them. We do this by describing and interpreting
        various negotiation situations and by developing formal constructs
        and theorems for determining the character of a negotiation situation.
        Key among these concepts is the notion of opposition. Although opposition
        is defined in terms of the utility functions, it is more fundamental
        in the sense that it is more intuitive to decision makers and can
        be used in contexts in which the parties' utilities are unknown or
        are partially known. The effects of various rationality assumptions
        on efficiency and their implications for negotiation support systems
        are discussed. We argue that the prescriptive/descriptive approach
        advocated by negotiation analysts lacks sufficient explanatory powers
        to be effectively used in negotiation support and that negotiation
        support systems should not constrain the parties to the set of efficient
        points.},
  acmid = {2229474},
  address = {Piscataway, NJ, USA},
  doi = {10.1109/3468.668964},
  issn = {1083-4427},
  issue_date = {May 1998},
  numpages = {13},
  publisher = {IEEE Press},
  url = {http://dx.doi.org/10.1109/3468.668964}
}

@ARTICLE{Ker03,
  author = {Gregory E. Kersten and Grant Zhang},
  title = {Mining Inspire Data for the Determinants of Successful Internet Negotiations},
  journal = {Central European Journal of Operational Research},
  year = {2003},
  volume = {11},
  pages = {297--316},
  number = {3},
  owner = {tim},
  timestamp = {2010.06.25}
}

@ARTICLE{Ket01,
  author = {Ketter, Wolfgang and Collins, John and Reddy, Prashant and Flath, Christoph and de Weerdt, Mathijs},
  title = {The Power Trading Agent Competition},
  journal = {ERIM Report Series Reference No. ERS-2011-027-LIS},
  year = {2011}
}

@ARTICLE{Kje05,
  author = {Kjerstad, Egil},
  title = {Auctions vs Negotiations: A Study of Price Differentials},
  journal = {Econometrics and Health Economics},
  year = {2005},
  volume = {14},
  pages = {1239-1251},
  number = {12}
}

@INPROCEEDINGS{Klau01,
  author = {Klaue, S. and Kurbel, K. and Loutchko, I.},
  title = {Automated negotiation on agent-based e-marketplaces: an overview},
  booktitle = {Proceedings of 14th Bled Electronic Commerce Conference},
  year = {2001},
  pages = {508--519},
  organization = {Citeseer},
  owner = {---},
  timestamp = {2011.06.24}
}

@article{Kle13,
title = "From problems to protocols: Towards a negotiation handbook",
journal = "Decision Support Systems",
volume = "60",
number = "0",
pages = "39--54",
year = "2014",
note = "Automated Negotiation Technologies and their Applications",
issn = "0167-9236",
doi = "http://dx.doi.org/10.1016/j.dss.2013.05.019",
url = "http://www.sciencedirect.com/science/article/pii/S016792361300167X",
author = "Ivan Marsa-Maestre and Mark Klein and Catholijn M. Jonker and Reyhan Aydo{\u{g}}an",
keywords = "Automated negotiation",
}

@ARTICLE{Kle03,
  author = {Klein, Mark and Faratin, Peyman and Sayama, Hiroki and Bar-Yam, Yaneer},
  title = {Negotiating Complex Contracts},
  journal = {Group Decision and Negotiation},
  year = {2003},
  volume = {12},
  pages = {111-125},
  abstract = {Work to date on computational models of negotiation has focused almost
        exclusively on defining contracts consisting of one or a few independent
        issues and tractable contract spaces. Many real-world contracts,
        by contrast, are much more complex, consisting of multiple inter-dependent
        issues and intractably large contract spaces. This paper describes
        a simulated annealing based approach appropriate for negotiating
        such complex contracts that achieves near-optimal social welfares
        for negotiations with binary issue dependencies.},
  issn = {0926-2644},
  issue = {2},
  keyword = {Business and Economics},
  publisher = {Springer Netherlands},
  url = {http://dx.doi.org/10.1023/A:1023068821218}
}

@ARTICLE{Kle89,
  author = {Mark Klein and Stephen C.-Y. Lu},
  title = {Conflict resolution in cooperative design},
  journal = {Artificial Intelligence in Engineering},
  year = {1989},
  volume = {4},
  pages = {168 - 180},
  number = {4},
  abstract = {Complex modern-day artifacts are designed by groups of experts, each
        with their own areas of expertise. Current approaches to group design
        are often serial and iterative in nature, which can be time-consuming
        as well as leading to poor designs that are expensive to realize.
        New models for cooperative group design, which emphasize the parallel
        interaction of the design experts involved, are needed. A central
        issue in cooperative group design concerns how conflicts among different
        experts can be resolved as the design is being produced. This paper
        proposes a model for how such conflict resolution can take place,
        and describes the results of a study aimed at verifying and instantiating
        this model by examining conflict resolution among human experts in
        the domain of architectural design. The study yielded four main conclusions:
        (1) conflict resolution plays a central role in cooperative design,
        (2) a rich collection of domain-independent conflict resolution expertise
        can be identified, (3) we need to represent the design rationale
        to support conflict resolution, and (4) knowledge acquisition in
        cooperative design presents special challenges and requires special
        techniques. We include a description of the conflict resolution expertise
        we uncovered. },
  doi = {http://dx.doi.org/10.1016/0954-1810(89)90013-7},
  issn = {0954-1810},
  keywords = {conflict resolution},
  url = {http://www.sciencedirect.com/science/article/pii/0954181089900137}
}

@ARTICLE{Klo10,
  author = {Tomas B. Klos and Koye Somefun and Johannes A. La Poutr{\'e}},
  title = {Automated Interactive Sales Processes},
  journal = {IEEE Intelligent Systems},
  year = {2011},
  volume = {26},
  pages = {54-61},
  number = {4},
  address = {Los Alamitos, CA, USA},
  doi = {http://doi.ieeecomputersociety.org/10.1109/MIS.2010.34},
  issn = {1541-1672},
  publisher = {IEEE Computer Society}
}

@ARTICLE{Kol12,
  author = {Kolomvatsos, Kostas and Hadjiefthymiades, Stathes},
  title = {Buyer behavior adaptation based on a fuzzy logic controller and prediction techniques},
  journal = {Fuzzy Sets and Systems},
  year = {2012},
  volume = {189},
  pages = {30--52},
  number = {1},
  owner = {Mark},
  publisher = {Elsevier},
  timestamp = {2013.02.02}
}

@article{Kol13,
 author = {Kolomvatsos, Kostas and Hadjieftymiades, Stathes},
 title = {On the Use of Particle Swarm Optimization and Kernel Density Estimator in Concurrent Negotiations},
 journal = {Information Sciences},
 issue_date = {March, 2014},
 volume = {262},
 month = {Mar},
 year = {2014},
 issn = {0020-0255},
 pages = {99--116},
 numpages = {18},
 url = {http://dx.doi.org/10.1016/j.ins.2013.10.025},
 doi = {10.1016/j.ins.2013.10.025},
 acmid = {2574660},
 publisher = {Elsevier Science Inc.},
 address = {New York, NY, USA},
 keywords = {Concurrent negotiations, Kernel density estimator, Particle Swarm Optimization, Swarm intelligence},
 abstract = {Abstract Electronic Marketplaces (EMs) can offer a number of advantages
        for users searching for products. In EMs, Intelligent Agents (IAs)
        can undertake the responsibility of representing buyers and sellers
        and negotiate over the conclusion of purchases. For this purpose,
        a negotiation is held between IAs. The most important characteristics
        are the deadline and the pricing strategy. The strategy defines the
        proposed prices at every round of the negotiation. We focus on the
        buyer side. We study concurrent negotiations between a buyer and
        a set of sellers. In this setting, the buyer utilizes a number of
        threads. Each thread follows a specific strategy and adopts swarm
        intelligence techniques for achieving the optimal agreement. The
        Particle Swarm Optimization (PSO) algorithm is adopted by each thread.
        Our architecture requires no central coordination. In real situations,
        there is absolutely no knowledge for the characteristics of the involved
        entities. In this paper, we model such kind of uncertainty through
        known techniques for estimating the distribution of deadlines and
        strategies. One of them is the Kernel Density Estimation (KDE) technique.
        Our experimental results depict the time interval where the agreement
        is possible and the efficiency of the proposed model. },
}

@article{Kol13optstop,
          volume = {99},
           month = {Sep},
           title = {Determining the optimal stopping time for automated negotiations},
          author = {Kostas Kolomvatsos and Christos Anagnostopoulos and Stathes Hadjiefthymiades},
            year = {2013},
           pages = {1--1},
         journal = {IEEE Transactions on Systems, Man, and Cybernetics: Systems},
             url = {http://eprints.gla.ac.uk/86008/},
        abstract = {Electronic markets are virtual frameworks where entities not known in advance have the opportunity to interact for the trading of products or services. Usually, a negotiation is necessary for the conclusion of the transaction. The conclusion is either positive (agreement) or negative (conflict). An efficient reasoning mechanism is necessary for players participating in negotiations. In this paper, we focus on the buyer side and propose two decision models based on the optimal stopping theory (OST). OST is proved to be very efficient in cases where an entity tries to find the time to stop a process with the aim of maximizing her utility. The outcome of the proposed decision method indicates whether the buyer stops a negotiation either by accepting the offer or continuing in the negotiation by rejecting it. In our models, we assume zero knowledge on the players' characteristics. Our proposed decision models do not require any complex modeling or any information provided by experts. Experimental results reveal the efficiency of each model and provide a comparison assessment with other research efforts.}
}

@INPROCEEDINGS{Kow10,
isbn={978-3-540-00742-5},
volume={2592},
author={Kowalczyk, Ryszard and Ulieru, Mihaela and Unland, Rainer},
  title = {Integrating mobile and intelligent agents in advanced E-commerce:
        A survey},
        doi={10.1007/3-540-36559-1_22},
        series={Lecture Notes in Computer Science},
  booktitle = {Agent Technologies, Infrastructures, Tools, and Applications for
        E-Services},
        editor={Carbonell, Jaime G. and Siekmann, J\"{o}rg and Kowalczyk, Ryszard and M\"{u}ller, J\"{o}rg P. and Tianfield, Huaglory and Unland, Rainer},
  year = {2003},
  pages = {295--313},
publisher={Springer Berlin Heidelberg},
  journal = {Agent Technologies, Infrastructures, Tools, and Applications for
        E-Services},
  owner = {---},
  timestamp = {2011.05.22}
}

@BOOK{Kra01,
  title = {Strategic Negotiation in Multiagent Environments},
  publisher = {MIT Press},
  year = {2001},
  author = {Kraus, Sarit},
  month = {Oct},
  abstract = {As computers advance from isolated workstations to linked elements
        in complex communities of systems and people, cooperation and coordination
        via intelligent agents become increasingly important. Examples of
        such communities include the Internet, electronic commerce, health
        institutions, electricity networks, and digital libraries. Sarit
        Kraus is concerned here with the cooperation and coordination of
        intelligent agents that are self-interested and usually owned by
        different individuals or organizations. Conflicts frequently arise,
        and negotiation is one of the main mechanisms for reaching agreement.
        Kraus presents a strategic-negotiation model that enables autonomous
        agents to reach mutually beneficial agreements efficiently in complex
        environments. The model, which integrates game theory, economic techniques,
        and heuristic methods of artificial intelligence, can be automated
        in computer systems or applied to human situations. The book provides
        both theoretical and experimental results.},
  citeulike-article-id = {3786351},
  howpublished = {Reli\'{e}},
  isbn = {0262112647},
  keywords = {multiagent},
  owner = {tim},
  posted-at = {2008-12-13 17:15:56},
  priority = {2},
  timestamp = {2010.03.16},
  url = {http://www.worldcat.org/isbn/0262112647}
}

@incollection{Kra01Decision,
 author = {Kraus, Sarit},
 chapter = {Automated Negotiation and Decision Making in Multiagent Environments},
 title = {Mutli-agents Systems and Applications},
 editor = {Carbonell, Jaime G. and Siekmann, J\"{o}org},
 year = {2001},
 isbn = {3-540-42312-5},
 pages = {150--172},
 numpages = {23},
 url = {http://dl.acm.org/citation.cfm?id=567248.567255},
 acmid = {567255},
 publisher = {Springer-Verlag New York, Inc.},
 address = {New York, NY, USA},
}

@ARTICLE{Kra97,
  author = {Sarit Kraus},
  title = {Negotiation and cooperation in multi-agent environments},
  journal = {Artificial Intelligence},
  year = {1997},
  volume = {94},
  pages = {79--97},
  number = {1-2},
  doi = {http://dx.doi.org/10.1016/S0004-3702(97)00025-8},
  issn = {0004-3702},
  keywords = {Distributed Artificial Intelligence},
  owner = {---},
  publisher = {Elsevier},
  url = {http://www.sciencedirect.com/science/article/pii/S0004370297000258}
}

@ARTICLE{Kra08,
  author = {Sarit Kraus and Penina Hoz-Weiss and Jonathan Wilkenfeld and David
        R. Andersen and Amy Pate},
  title = {Resolving crises through automated bilateral negotiations },
  journal = {Artificial Intelligence },
  year = {2008},
  volume = {172},
  pages = {1 - 18},
  number = {1},
  abstract = {We describe the development of an automated agent that can negotiate
        efficiently with people in crises. The environment is characterized
        by two negotiators, time constraints, deadlines, full information,
        and the possibility of opting out. The agent can play either role,
        with communications via a pre-defined language. The model used in
        constructing the agent is based on a formal analysis of the crises
        scenario using game-theoretic methods and heuristics for bargaining.
        The agent receives messages sent by its opponent, analyzes them and
        responds. It also initiates discussion on one or more parameters
        of an agreement. Experimental results of simulations of a fishing
        dispute between Canada and Spain indicate that the agent played at
        least as well as, and in the case of Spain, significantly better
        than a human player. },
  doi = {10.1016/j.artint.2007.05.007},
  issn = {0004-3702},
  keywords = {Bilateral negotiation},
  url = {http://www.sciencedirect.com/science/article/pii/S0004370207001051}
}

@ARTICLE{KraLeh95,
  author = {Sarit Kraus and Daniel Lehmann},
  title = {Designing and Building a Negotiating Automated Agent},
  journal = {Computational Intelligence},
  year = {1995},
  volume = {11},
  publisher = {Blackwell Publishing Ltd},
  pages = {132-171},
  doi = {10.1111/j.1467-8640.1995.tb00026.x},
  issn = {1467-8640},
  number = {1}
}

@ARTICLE{Kra92,
  author = {S. Kraus and J. Wilkenfeld and M.A. Harris and E. Blake},
  title = {The Hostage Crisis Simulation},
  journal = {Simulation \& Gaming},
  year = {1992},
  volume = {23},
  pages = {398-416},
  number = {4}
}

@ARTICLE{Kra95,
  author = {Sarit Kraus and Jonathan Wilkenfeld and Gilad Zlotkin},
  title = {Multiagent negotiation under time constraints},
  journal = {Artificial Intelligence},
  year = {1995},
  volume = {75},
  pages = {297 - 345},
  number = {2},
  abstract = {Research in distributed artificial intelligence (DAI) is concerned
        with how automated agents can be designed to interact effectively.
        Negotiation is proposed as a means for agents to communicate and
        compromise to reach mutually beneficial agreements. The paper examines
        the problems of resource allocation and task distribution among autonomous
        agents which can benefit from sharing a common resource or distributing
        a set of common tasks. We propose a strategic model of negotiation
        that takes the passage of time during the negotiation process itself
        into account. A distributed negotiation mechanism is introduced that
        is simple, efficient, stable, and flexible in various situations.
        The model considers situations characterized by complete as well
        as incomplete information, and ones in which some agents lose over
        time while others gain over time. Using this negotiation mechanism
        autonomous agents have simple and stable negotiation strategies that
        result in efficient agreements without delays even when there are
        dynamic changes in the environment.},
  doi = {DOI: 10.1016/0004-3702(94)00021-R},
  issn = {0004-3702},
  owner = {tim},
  timestamp = {2010.03.03},
  url = {http://www.sciencedirect.com/science/article/B6TYF-409W4BC-N/2/597d666d5362ae944329068f88fefa3e}
}

@INCOLLECTION{ANAC2011Kri,
  author = {van Krimpen, Thijs and Looije, Daphne and Hajizadeh, Siamak},
  title = {HardHeaded},
  booktitle = {Complex Automated Negotiations: Theories, Models, and Software Competitions},
  publisher = {Springer Berlin Heidelberg},
  year = {2013},
  editor = {Ito, Takayuki and Zhang, Minjie and Robu, Valentin and Matsuo, Tokuro},
  volume = {435},
  series = {Studies in Computational Intelligence},
  pages = {223-227},
  doi = {10.1007/978-3-642-30737-9\_17},
  isbn = {978-3-642-30736-2},
  url = {http://dx.doi.org/10.1007/978-3-642-30737-9\_17}
}

@INCOLLECTION{ANAC2011Krishort,
  author = {van Krimpen, Thijs and Looije, Daphne and Hajizadeh, Siamak},
  title = {HardHeaded},
  booktitle = {Complex Automated Negotiations: Theories, Models, and Software Competitions},
  publisher = {Springer Berlin Heidelberg},
  year = {2013},
  pages = {223-227},
  doi = {10.1007/978-3-642-30737-9\_17},
  isbn = {978-3-642-30736-2},
  url = {http://dx.doi.org/10.1007/978-3-642-30737-9\_17}
}

@INCOLLECTION{ANAC2011Krishorter,
  author = {van Krimpen, Thijs and Looije, Daphne and Hajizadeh, Siamak},
  title = {HardHeaded},
  booktitle = {Complex Automated Negotiations: Theories, Models, and Software Competitions},
  publisher = {Springer Berlin Heidelberg},
  year = {2013},
  isbn = {978-3-642-30736-2},
  owner = {Mark},
  timestamp = {2013.04.20}
}

@MISC{Kro93,
  author = {Ben Kr\"{o}se and Patrick van der Smagt},
  title = {An introduction to Neural Networks},
  year = {1993},
  owner = {---},
  timestamp = {2011.06.18}
}

@ARTICLE{Kro99,
  author = {Krovi, R. and Graesser, A.C. and Pracht, William E.},
  title = {Agent behaviors in virtual negotiation environments},
  journal = {IEEE Transactions on Systems, Man, and Cybernetics, Part C: Applications and Reviews},
  year = {1999},
  volume = {29},
  pages = {15-25},
  number = {1},
  abstract = {A computational prototype of negotiation behavior is presented where
        the following occurs: (1) agents employ different concession matching
        tactics; (2) agents are unaware of opponent preferences; (3) agents
        incur a cost for delaying settlements; (4) agents vary in terms of
        goal difficulty and initial offer magnitude; and (5) demands and
        counter-offers are made and evaluated based on the opponent's degree
        of concession matching. This research explores the impact of the
        interaction of different agent behaviors on the negotiation process
        and the outcome of the negotiation. Simulation experiments show that
        the prototype is able to manifest fundamental patterns and confirms
        the effectiveness of classical negotiation and mediation strategies,
        such as ambitious goals and aggressive concession matching tactics.
        The model reveals some counterintuitive patterns that may shed a
        new perspective on the effects of time constraints and information
        availability},
  doi = {10.1109/5326.740666},
  issn = {1094-6977},
  keywords = {adaptive systems;behavioural sciences computing;cognitive systems;digital
        simulation;distributed decision making;genetic algorithms;multi-agent
        systems;negotiation support systems;social sciences computing;adaptive
        systems;agent behaviors;aggressive tactics;ambitious goals;behavioral
        simulation;cognitive modeling;computational models;computational
        prototype;concession matching tactics;counter-offers;demands;distributed
        decision making;fundamental patterns;goal difficulty;information
        availability;initial offer magnitude;mediation strategies;negotiation
        behavior;opponent preferences;organizational models;settlement delay
        cost;time constraints;virtual negotiation environments;Computational
        modeling;Costs;Decision making;Delay;Mediation;Neurons;Pattern matching;Prototypes;Time
        factors;Virtual prototyping}
}

@ARTICLE{Kun75,
  author = {Kung, H.T. and Luccio, F. and Preparata, F.P.},
  title = {On Finding the Maxima of a Set of Vectors},
  journal = {J. ACM},
  year = {1975},
  volume = {22},
  pages = {469--476},
  month = {Oct},
  acmid = {321910},
  address = {New York, NY, USA},
  doi = {http://doi.acm.org/10.1145/321906.321910},
  issn = {0004-5411},
  issue = {4},
  numpages = {8},
  owner = {tim},
  publisher = {ACM},
  timestamp = {2011.02.18},
  url = {http://doi.acm.org/10.1145/321906.321910}
}

@INPROCEEDINGS{Kur01,
  author = {Kurbel, K. and Loutchko, I.},
  title = {A framework for multi-agent electronic marketplaces: analysis and
        classification of existing systems},
  booktitle = {Proceedings of International ICSC Congress on Information Science
        Innovations},
  year = {2001},
  organization = {Citeseer},
  owner = {---},
  timestamp = {2011.07.03}
}

@TECHREPORT{Lai04,
  author = {Lai, Guoming and Li, Cuihong and Sycara, Katia P. and Giampapa, Joseph
        Andrew},
  title = {Literature Review on Multi-attribute Negotiations},
  institution = {Robotics Institute, Carnegie Mellon University},
  year = {2004},
  month = {Dec}
}

@ARTICLE{Lai09,
  author = {Lai, Guoming and Sycara, Katia P.},
  title = {A Generic Framework for Automated Multi-attribute Negotiation},
  journal = {Group Decision and Negotiation},
  year = {2009},
  volume = {18},
  pages = {169-187},
  number = {2}
}

@ARTICLE{Lai08,
  author = {Lai, Guoming and Sycara, Katia P. and Li, Cuihong},
  title = {A decentralized model for automated multi-attribute negotiations
        with incomplete information and general utility functions},
  journal = {Multiagent and Grid Systems},
  year = {2008},
   month = {Jan},
  volume = {4},
  pages = {45--65},
  number = {1},
  owner = {Mark},
  publisher = {IOS Press},
   address = {Amsterdam, The Netherlands},
  timestamp = {2013.06.02}
}

@INPROCEEDINGS{Lai06decentralized,
  author = {Lai, Guoming and Sycara, Katia P. and Li, Cuihong},
  title = {A decentralized model for multi-attribute negotiations},
  booktitle = {Proceedings of the 8th international conference on Electronic commerce:
        The new e-commerce: innovations for conquering current barriers,
        obstacles and limitations to conducting successful business on the
        internet},
  year = {2006},
  series = {ICEC '06},
  pages = {3--10},
  address = {New York, NY, USA},
  publisher = {ACM},
  acmid = {1151471},
  doi = {10.1145/1151454.1151471},
  isbn = {1-59593-392-1},
  keywords = {automated negotiation, multi-attribute negotiation, pareto optimality,
        performance analysis, rational preference},
  location = {Fredericton, New Brunswick, Canada},
  numpages = {8},
  owner = {Mark},
  timestamp = {2013.06.02},
  url = {http://doi.acm.org/10.1145/1151454.1151471}
}

@ARTICLE{Lai06,
  author = {Lai, Hsiangchu and Doong, Her-Sen and Kao, Chi-Chung and Kersten,
        Gregory E.},
  title = {Negotiators' Communication, Perception of Their Counterparts, and
        Performance in Dyadic E-negotiations},
  journal = {Group Decision and Negotiation},
  year = {2006},
  volume = {15},
  pages = {429-447},
  abstract = {The aim of this study was to improve our understanding of negotiation
        strategies, behaviors, and outcomes, and the relationships between
        these factors based on data collected from questionnaires, actual
        behavior during the negotiation process implemented using e-negotiation
        system, and the negotiation outcomes. This study clustered the negotiators
        based on either the negotiators' own strategies or their thoughts
        about those of their partners. This resulted in a division into cooperative
        and noncooperative clusters. We found that the negotiators whose
        own strategies are less cooperative tend to submit more offers but
        fewer messages. However, these people consIDer that they have less
        control over the negotiation process compared with those who adopt
        a more cooperative strategy, who make fewer offers but send more
        messages. Those in the cooperative cluster consistently feel friendlier
        about the negotiation and more satisfied with the outcome and their
        performance. Further, there is a correlation not only between self-strategies
        and the thoughts about partners' strategies, but also between strategies
        and final agreements. Finally, the proportion of negotiations reaching
        agreement is larger for the cooperative cluster than for the noncooperative
        cluster.},
  affiliation = {National Sun Yat-sen University Kaohsiung Taiwan Kaohsiung Taiwan},
  issn = {0926-2644},
  issue = {5},
  keyword = {Humanities, Social Sciences and Law},
  owner = {tim},
  publisher = {Springer Netherlands},
  timestamp = {2011.06.16},
  url = {http://dx.doi.org/10.1007/s10726-006-9037-7}
}

@BOOK{Lar04,
  title = {Applying UML and Patterns: An Introduction to Object-Oriented Analysis
        and Design and Iterative Development},
  publisher = {Prentice Hall PTR },
  year = {2004},
  author = {Larman, Craig}
}

@INCOLLECTION{Lau09,
  author = {Lau, Raymond Y.K.},
  title = {An Evolutionary Approach for Intelligent Negotiation Agents in e-Marketplaces},
  booktitle = {Intelligent Agents in the Evolution of Web and Applications},
  publisher = {Springer Berlin Heidelberg},
  year = {2009},
  editor = {Nguyen, Ngoc and Jain, Lakhmi},
  volume = {167},
  series = {Studies in Computational Intelligence},
  pages = {279-301},
  affiliation = {City University of Hong Kong Department of Information Systems Tat
        Chee Avenue, Kowloon Hong Kong SAR},
  isbn = {978-3-540-88070-7},
  keyword = {Engineering},
  owner = {Mark},
  timestamp = {2013.02.08}
}

@ARTICLE{Lau05Evolutionary,
 author = {Lau, Raymond Y.K. and Tang, Maolin and Wong, On and Milliner, Stephen W. and Chen, Yi-Ping Phoebe},
  title = {An evolutionary learning approach for adaptive negotiation agents},
  journal = {International journal of intelligent systems},
  year = {2006},
  volume = {21},
  pages = {41--72},
   month = {Jan},
    issn = {0884-8173},
  number = {1},
  owner = {Mark},
   doi = {10.1002/int.v21:1},
 publisher = {John Wiley \& Sons, Inc.},
  timestamp = {2013.01.18},
   address = {New York, NY, USA}
}

@ARTICLE{Lau08Mining,
  author = {Lau, Raymond Y.K. and Wong, On and Li, Yuefeng and Ma, Louis},
  title = {Mining Trading Partners' Preferences for Efficient Multi-Issue Bargaining
        in E-Business},
  journal = {J. Manage. Inf. Syst.},
  year = {2008},
  volume = {25},
  pages = {79--104},
  month = {Jul},
  acmid = {1481795},
  address = {Armonk, NY, USA},
  issn = {0742-1222},
  issue = {1},
  numpages = {26},
  owner = {Mark},
  publisher = {M. E. Sharpe, Inc.},
  timestamp = {2013.02.08}
}

@ARTICLE{Lau08,
  author = {Raymond Y.K. Lau and Yuefeng Li and Dawei Song and Ron Chi-Wai Kwok},
  title = {Knowledge discovery for adaptive negotiation agents in e-marketplaces},
  journal = {Decision Support Systems},
  year = {2008},
  volume = {45},
  pages = {310--323},
  number = {2},
  doi = {http://dx.doi.org/10.1016/j.dss.2007.12.018},
  issn = {0167-9236},
  keywords = {Knowledge discovery},
  owner = {Mark},
  publisher = {Elsevier},
  timestamp = {2013.01.23},
  url = {http://www.sciencedirect.com/science/article/pii/S016792360800002X}
}

@INPROCEEDINGS{Lau05,
  author = {Lau, Raymond Y.K.},
  title = {Adaptive negotiation agents for e-business},
  booktitle = {Proceedings of the 7th international conference on Electronic commerce},
  year = {2005},
  series = {ICEC '05},
  pages = {271--278},
  address = {New York, NY, USA},
  publisher = {ACM},
  acmid = {1089604},
  doi = {10.1145/1089551.1089604},
  isbn = {1-59593-112-0},
  keywords = {automated negotiation, e-business, evolutionary learning, intelligent
        agents},
  location = {Xi'an, China},
  numpages = {8},
  url = {http://doi.acm.org/10.1145/1089551.1089604}
}

@INCOLLECTION{Lax1992,
  author = {D.A. Lax and J.K. Sebenius},
  title = {Thinking coalitionally: party arithmetic, process opportunism, and
        strategic sequencing},
  booktitle = {Negotiation Analysis},
  publisher = {The University of Michigan Press},
  year = {1992},
  editor = {H.P. Young},
  pages = {153-193}
}

@ARTICLE{Lee09,
  author = {Chun Ching Lee and Chao Ou-Yang},
  title = {A neural networks approach for forecasting the supplier's bid prices
        in supplier selection negotiation process},
  journal = {Expert Systems with Applications},
  year = {2009},
  volume = {36},
  pages = {2961--2970},
  number = {2, Part 2},
  doi = {http://dx.doi.org/10.1016/j.eswa.2008.01.063},
  issn = {0957-4174},
  keywords = {Supplier selection negotiation process},
  owner = {Mark},
  publisher = {Elsevier},
  timestamp = {2013.02.01},
  url = {http://www.sciencedirect.com/science/article/pii/S0957417408000468}
}

@BOOK{Leo73,
  title = {To stop or not to stop. Some elementary optimal stopping problems
        with economic interpretations},
  publisher = { Almqvist \& Wiksell, Stockholm },
  year = { 1973 },
  author = { Leonardz, Bj\"{o}rn},
  pages = { 178 p. },
  catalogue-url = { http://nla.gov.au/nla.cat-vn252403 },
  isbn = { 9120038054 },
  language = { English },
  life-dates = { 1973 - },
  subjects = { Decision-making - Mathematical models.; Optimal stopping (Mathematical
        statistics) },
  type = { Book }
}

@BOOK{Lew03,
  title = {Essentials of Negotiation},
  publisher = {McGraw-Hill},
  year = {2003},
  author = {Lewicki, Roy J. and Saunders, David M. and Barry, Bruce and Minton, John W.},
  address = {Boston, MA},
  citeulike-article-id = {1471404},
  keywords = {argumentation},
  owner = {tim},
  posted-at = {2007-07-21 16:19:07},
  priority = {0},
  timestamp = {2011.05.31}
}

@ARTICLE{Li06,
  author = {Cuihong Li and Joseph Giampapa and Katia P. Sycara},
  title = {Bilateral negotiation decisions with uncertain dynamic outside options},
  journal = {IEEE Transactions on Systems, Man, and Cybernetics, Part C: Applications and Reviews},
  year = {2006},
  volume = {36},
  pages = {31-44},
  number = {1},
  month = {Jan},
  abstract = {We present a model for bilateral negotiations that considers the uncertain
        and dynamic outside options. Outside options affect the negotiation
        strategies via their impact on the reservation price. The model is
        composed of three modules: single-threaded negotiations, synchronized
        multithreaded negotiations, and dynamic multithreaded negotiations.
        These three modules embody increased sophistication and complexity.
        The single-threaded negotiation model provides negotiation strategies
        without specifically considering outside options. The model of synchronized
        multithreaded negotiations builds on the single-threaded negotiation
        model and considers the presence of concurrently existing outside
        options. The model of dynamic multithreaded negotiations expands
        the synchronized multithreaded model by considering the uncertain
        outside options that may come dynamically in the future. Experimental
        analysis is provided to characterize the impact of outside options
        on the reservation price and thus on the negotiation strategy. The
        results show that the utility of a negotiator improves significantly
        if he/she considers outside options, and the average utility is higher
        when he/she considers both the concurrent outside options and the
        foresees future options},
  doi = {10.1109/TSMCC.2005.860573},
  issn = {1094-6977},
  keywords = {decision making;multi-agent systems;negotiation support systems;bilateral
        negotiation decision;dynamic multithreaded negotiation;reservation
        price;single-threaded negotiation;synchronized multithreaded negotiation;uncertain
        dynamic outside option;Billets;Cost accounting;Displays;Intelligent
        agent;Intelligent robots;Laboratories;Personnel;Software agents;Subcontracting}
}

@MISC{Li04,
  author = {Cuihong Li and Joseph Giampapa and Katia P. Sycara},
  title = {Bilateral negotiation decisions with uncertain dynamic outside options},
  year = {2004},
  pages = {54-61}
}

@TECHREPORT{Li03,
  author = {Li, Cuihong and Giampapa, Joseph and Sycara, Katia P.},
  title = {A review of research literature on bilateral negotiations},
  institution = {Robotics Institute},
  year = {2003},
  address = {Pittsburgh, PA},
  month = {Nov},
  owner = {---},
  publisher = {Citeseer},
  timestamp = {2011.08.18}
}

@INPROCEEDINGS{Li04MAS,
  author = {Li, J. and Cao, Y.D.},
  title = {Bayesian learning in bilateral multi-issue negotiation and its application
        in MAS-based electronic commerce},
  booktitle = {Proceedings IEEE/WIC/ACM
        International Conference on Intelligent Agent Technology},
  year = {2004},
  pages = {437--440},
  organization = {IEEE},
  owner = {Mark},
  timestamp = {2013.01.25}
}

@ARTICLE{Li08,
  author = {Li, J. and Wang, C. and Yang, Y.},
  title = {An adaptive genetic algorithm and its application in bilateral multi-issue
        negotiation},
  journal = {The Journal of China Universities of Posts and Telecommunications},
  year = {2008},
  volume = {15},
  pages = {94--97},
  owner = {Mark},
  publisher = {Elsevier},
  timestamp = {2013.01.27}
}

@ARTICLE{Li11,
  author = {Li, M. and Vo, Q.B. and Kowalczyk, R.},
  title = {Majority-rule-based preference aggregation on multi-attribute domains
        with {CP}-nets},
  journal = {compare},
  year = {2011},
  volume = {210},
  pages = {2},
  owner = {Mark},
  timestamp = {2013.02.09}
}

@INPROCEEDINGS{Li09,
  author = {Li, M. and Vo, Q.B. and Kowalczyk, R.},
  title = {Searching for fair joint gains in agent-based negotiation},
  booktitle = {Proceedings of The 8th International Conference on Autonomous Agents
        and Multiagent Systems},
        volume = {2},
  year = {2009},
  pages = {1049--1056},
  organization = {International Foundation for Autonomous Agents and Multiagent Systems},
  owner = {Mark},
  timestamp = {2013.02.11}
}

@INPROCEEDINGS{Lia08,
  author = {{Yong-quan} Liang and Yong Yuan},
  title = {Co-evolutionary stability in the alternating-offer negotiation},
  booktitle = {IEEE Conference on Cybernetics and Intelligent Systems},
  year = {2008},
  month={Sep},
  pages = {1176-1180},
  doi = {10.1109/ICCIS.2008.4670896},
  keywords = {electronic commerce;game theory;genetic algorithms;alternating-offer
        negotiation;automatic acquisition;coevolutionary stability;e-commerce
        negotiations;evolutionary game theory;evolutionary genetic algorithm;replicator
        dynamics;subgame perfect equilibrium;Bioinformatics;Educational institutions;Electronic
        switching systems;Game theory;Genetic mutations;Genomics;Information
        science;Learning systems;Protocols;Stability analysis;Alternating
        offer;Evolutionary game;Replicator dynamics;Sub-game perfect equilibrium}
}

@ARTICLE{Lin13,
  author = {Raz Lin and Ya'akov (Kobi) Gal and Sarit Kraus and Yaniv Mazliah},
  title = {Training with automated agents improves people's behavior in negotiation     and coordination tasks},
  journal = {Decision Support Systems },
  year = {2013},
  doi = {http://dx.doi.org/10.1016/j.dss.2013.05.015},
  issn = {0167-9236},
  url = {http://www.sciencedirect.com/science/article/pii/S0167923613001632}
}

@ARTICLE{Linanimed,
  author = {Lin, Raz and Gev, Yehoshua and Kraus, Sarit},
  title = {AniMed*: An Automated Animated Mediator for Facilitating Negotiation
        with People}
}

@ARTICLE{Lin11,
  author = {Lin, Raz and Gev, Yehoshua and Kraus, Sarit},
  title = {Bridging the Gap: Face-to-Face Negotiations with an Automated Mediator},
  journal = {IEEE Intelligent Systems},
  year = {2011},
  volume = {26},
  pages = {40--47},
  number = {6},
  publisher = {Institute of Electrical and Electronics Engineers, Inc., USA United
        States}
}

@ARTICLE{Lin11facilitating,
  author = {Lin, Raz and Gev, Yehoshua and Kraus, Sarit},
  title = {Facilitating Better Negotiation Solutions using AniMed},
  journal = {Proc. of Agent-based Complex Automated Negotiations},
  year = {2011},
  pages = {64--70}
}

@INCOLLECTION{Lin12Practice,
  author = {Lin, Raz and Kraus, Sarit},
  title = {From Research to Practice: Automated Negotiations with People},
  booktitle = {Ubiquitous Display Environments},
  publisher = {Springer Berlin Heidelberg},
  year = {2012},
  editor = {Kr\"uger, Antonio and Kuflik, Tsvi},
  series = {Cognitive Technologies},
  pages = {195-212},
  doi = {10.1007/978-3-642-27663-7\_12},
  isbn = {978-3-642-27662-0},
  language = {English},
  owner = {Mark},
  timestamp = {2013.02.11},
  url = {http://dx.doi.org/10.1007/978-3-642-27663-7\_12}
}

@book{Linh92,
  title={Bargaining with incomplete information},
  author={Linhart, P.B. and Radner, R. and Satterthwaite, M.A.},
  isbn={9780124510500},
  lccn={lc92011473},
  series={Economic theory, econometrics, and mathematical economics},
  url={https://books.google.nl/books?id=Ny25AAAAIAAJ},
  year={1992},
  publisher={Academic Press}
}

@ARTICLE{Lin10,
  author = {Lin, Raz and Kraus, Sarit},
  title = {Can automated agents proficiently negotiate with humans?},
  journal = {Communications of the ACM},
  year = {2010},
  volume = {53},
  pages = {78--88},
  number = {1},
  month = {Jan},
  acmid = {1629199},
  address = {New York, NY, USA},
  doi = {10.1145/1629175.1629199},
  issn = {0001-0782},
  numpages = {11},
  publisher = {ACM},
  url = {http://doi.acm.org/10.1145/1629175.1629199}
}

@ARTICLE{Lin12,
  author = {Raz Lin and Sarit Kraus and Tim Baarslag and Dmytro Tykhonov and Koen V. Hindriks and Catholijn M. Jonker},
  title = {Genius: An Integrated Environment for Supporting the Design of Generic Automated Negotiators},
  journal = {Computational Intelligence},
  year = {2014},
  volume = {30},
  pages = {48--70},
  number = {1},
  abstract = {The design of automated negotiators has been the focus of abundant
        research in recent years. However, due to difficulties involved in
        creating generalized agents that can negotiate in several domains
        and against human counterparts, many automated negotiators are domain
        specific and their behavior cannot be generalized for other domains.
        Some of these difficulties arise from the differences inherent within
        the domains, the need to understand and learn negotiators' diverse
        preferences concerning issues of the domain, and the different strategies
        negotiators can undertake. In this paper we present a system that
        enables alleviation of the difficulties in the design process of
        general automated negotiators termed Genius, a General Environment
        for Negotiation with Intelligent multi-purpose Usage Simulation.
        With the constant introduction of new domains, e-commerce and other
        applications, which require automated negotiations, generic automated
        negotiators encompass many benefits and advantages over agents that
        are designed for a specific domain. Based on experiments conducted
        with automated agents designed by human subjects using Genius we
        provide both quantitative and qualitative results to illustrate its
        efficacy. Finally, we also analyze a recent automated bilateral negotiators
        competition that was based on Genius. Our results show the advantages
        and underlying benefits of using Genius and how it can facilitate
        the design of general automated negotiators.},
  doi = {10.1111/j.1467-8640.2012.00463.x},
  issn = {1467-8640},
  keywords = {agents competition, automated negotiation, human/computer interaction,
        bilateral negotiation},
  publisher = {Blackwell Publishing Inc},
  url = {http://dx.doi.org/10.1111/j.1467-8640.2012.00463.x}
}

@INPROCEEDINGS{Lin09,
  author = {Raz Lin and Sarit Kraus and Dmytro Tykhonov and Koen V. Hindriks and Catholijn M. Jonker},
  title = {Supporting the Design of General Automated Negotiators},
  booktitle = {Proceedings of the Second International Workshop on Agent-based Complex
        Automated Negotiations (ACAN'09)},
  year = {2011},
  volume = {319},
  pages = {69 - 87},
  organization = {Springer},
  publisher = {Springer},
  abstract = {The design of automated negotiators has been the focus of abundant
        research in recent years. However and due to difficulties involved
        in creating generalized agents that can negotiate in several domains
        and against human counterparts and many automated negotiators are
        domain specific and their behavior cannot be generalized for other
        domains. Some of these difficulties arise from the differences inherent
        within the domains and the need to understand and learn negotiators'
        diverse preferences concerning issues of the domain and the different
        strategies negotiators can undertake. In this paper we present a
        system that enables alleviation of the difficulties in the design
        process of general automated negotiators termed GENIUS and a General
        Environment for Negotiation with Intelligent multi-purpose Usage
        Simulation. With the constant introduction of new domains and e-commerce
        and other applications and which require automated negotiations and
        generic automated negotiators encompass many benefits and advantages
        over agents that are designed for a specific domain. Based on experiments
        conducted with automated agents designed by human subjects using
        GENIUS we provide both quantitative and qualitative results to illustrate
        its efficacy. Our results show the advantages and underlying benefits
        of using GENIUS for designing general automated negotiators.},
  isbn = {978-3-642-15612-0},
  owner = {tim},
  timestamp = {2010.02.19},
  url = {http://ii.tudelft.nl/pub/dmytro/linetal-agentDesign.pdf}
}

@ARTICLE{Lin08,
  author = {Raz Lin and Sarit Kraus and Jonathan Wilkenfeld and James Barry},
  title = {Negotiating with bounded rational agents in environments with incomplete     information using an automated agent},
  journal = {Artificial Intelligence},
  year = {2008},
  volume = {172},
  pages = {823 - 851},
  number = {6-7},
  abstract = {Many tasks in day-to-day life involve interactions among several people.
        Many of these interactions involve negotiating over a desired outcome.
        Negotiation in and of itself is not an easy task, and it becomes
        more complex under conditions of incomplete information. For example,
        the parties do not know in advance the exact tradeoff of their counterparts
        between different outcomes. Furthermore information regarding the
        preferences of counterparts might only be elicited during the negotiation
        process itself. In this paper we propose a model for an automated
        negotiation agent capable of negotiating with bounded rational agents
        under conditions of incomplete information. We test this agent against
        people in two distinct domains, in order to verify that its model
        is generic, and thus can be adapted to any domain as long as the
        negotiators' preferences can be expressed in additive utilities.
        Our results indicate that the automated agent reaches more agreements
        and plays more effectively than its human counterparts. Moreover,
        in most of the cases, the automated agent achieves significantly
        better agreements, in terms of individual utility, than the human
        counterparts playing the same role.},
  doi = {DOI: 10.1016/j.artint.2007.09.007},
  issn = {0004-3702},
  keywords = {Bilateral negotiation},
  owner = {tim},
  timestamp = {2010.06.25},
  url = {http://www.sciencedirect.com/science/article/B6TYF-4PXDM5C-1/2/f581bc1e3326b51dc434c318f290cf02}
}

@INPROCEEDINGS{Lin06,
  author = {Lin, Raz and Kraus, Sarit and Wilkenfeld, Jonathan and Barry, James},
  title = {An Automated Agent for Bilateral Negotiation with Bounded Rational
        Agents with Incomplete Information},
  booktitle = {Proceedings of the 2006 conference on ECAI 2006: 17th European Conference
        on Artificial Intelligence},
  year = {2006},
  pages = {270--274},
  address = {Amsterdam, The Netherlands, The Netherlands},
  publisher = {IOS Press},
  acmid = {1567078},
  isbn = {1-58603-642-4},
  numpages = {5},
  url = {http://dl.acm.org/citation.cfm?id=1567016.1567078}
}

@INPROCEEDINGS{Lin09aamas,
  author = {Lin, Raz and Oshrat, Yinon and Kraus, Sarit},
  title = {Investigating the benefits of automated negotiations in enhancing
        people's negotiation skills},
  booktitle = {AAMAS '09: Proceedings of The 8th International Conference on Autonomous Agents
        and Multiagent Systems},
  year = {2009},
  pages = {345--352},
  isbn = {978-0-9817381-6-1},
  location = {Budapest, Hungary},
  owner = {tim},
  publisher = {International Foundation for Autonomous Agents and Multiagent Systems},
 address = {Richland, SC},
  timestamp = {2010.08.03}
}

@ARTICLE{Lit06,
  author = {Littman, Michael and Zinkevich, Martin},
  title = {The 2006 {AAAI} computer poker competition},
  journal = {ICGA Journal},
  year = {2006},
  volume = {29},
  pages = {166},
  number = {3}
}

@INCOLLECTION{Lom01,
  author = {Lomuscio, Alessio R. and Wooldridge, Michael J. and Jennings, Nicholas R.},
  title = {A Classification Scheme for Negotiation in Electronic Commerce},
  booktitle = {Agent Mediated Electronic Commerce},
  publisher = {Springer Berlin Heidelberg},
  year = {2001},
  editor = {Dignum, Frank and Sierra, Carles},
  volume = {1991},
  series = {Lecture Notes in Computer Science},
  pages = {19-33},
  abstract = {In the last few years we have witnessed a surge of business-to-consumer
        and business-to-business commerce operated on the Internet. However
        many of these systems are often nothing more than electronic catalogues
        on which the user can choose a product which is made available for
        a fixed price. This modus operandi is clearly failing to exploit
        the full potential of electronic commerce. Against this background,
        we argue here that in the next few years we will see a new generation
        of systems emerge, based on automatic negotiation. In this paper
        we identify the main parameters on which any automatic negotiation
        depends. This classification schema is then used to categorise the
        subsequent papers in this book that focus on automatic negotiation.},
  affiliation = {Imperial College of Science, Technology and Medicine Department of
        Computing SW7 2BZ London UK},
  owner = {tim},
  timestamp = {2011.05.25},
  url = {http://dx.doi.org/10.1007/3-540-44682-6\_2}
}

@ARTICLE{Lom03,
  author = {Lomuscio, Alessio R. and Wooldridge, Michael J. and Jennings, Nicholas R.},
  title = {A Classification Scheme for Negotiation in Electronic Commerce},
  journal = {Group Decision and Negotiation},
  year = {2003},
  volume = {12},
  pages = {31-56},
  number = {1},
  doi = {10.1023/A:1022232410606},
  issn = {0926-2644},
  language = {English},
  publisher = {Kluwer Academic Publishers},
  url = {http://dx.doi.org/10.1023/A%3A1022232410606}
}

@INPROCEEDINGS{Lop01,
author={Lopes, F. and Mamede, N. and Novais, A.Q. and Coelho, H.},
booktitle={12th International Workshop on Database and Expert Systems Applications, 2001. Proceedings.},
title={Negotiation tactics for autonomous agents},
year={2001},
pages={708-714},
abstract={Autonomous agents are being increasingly used in a wide range of applications. The agents operate in common environments and, over time, conflicts inevitably occur among them. Negotiation is the predominant process for solving conflicts. Recent growing interest in electronic commerce has also given increased importance to negotiation. This paper presents a generic negotiation mechanism that handles multiparty, multi-issue and single or repeated rounds and introduces a set of negotiation tactics that express the initial attitude of the agents and generate counterproposals either by making or not making concessions},
keywords={electronic commerce;multi-agent systems;agent conflicts;autonomous agents;common environments;e-commerce;electronic commerce;multiparty multi-issue negotiation;negotiation tactics;Autonomous agents;Electronic commerce;Libraries;Process planning;Strategic planning},
doi={10.1109/DEXA.2001.953141},
}

@ARTICLE{Lop12,
  author = {Lopez-Carmona, Miguel A. and Marsa-Maestre, Ivan and Klein, Mark and Ito, Takayuki},
  title = {Addressing stability issues in mediated complex contract negotiations for constraint-based, non-monotonic utility spaces},
  journal = {Autonomous Agents and Multi-Agent Systems},
  year = {2012},
  volume = {24},
  pages = {485-535},
  number = {3},
  doi = {10.1007/s10458-010-9159-9},
  issn = {1387-2532},
  keywords = {Automated multi-issue negotiation; Complex utility spaces; Strategy
        analysis},
  language = {English},
  publisher = {Springer US},
  url = {http://dx.doi.org/10.1007/s10458-010-9159-9}
}

@ARTICLE{Luo03,
  author = {Luo, Xudong and Jennings, Nicholas R. and Shadbolt, Nigel and Leung, Ho-fung and Lee, Jimmy Ho-man},        
  title = {A fuzzy constraint based model for bilateral, multi-issue negotiations in semi-competitive environments},
  journal = {Artificial Intelligence},
  year = {2003},
  volume = {148},
  pages = {53--102},
  number = {1},
  owner = {Mark},
  publisher = {Elsevier},
  timestamp = {2013.02.01}
}

@ARTICLE{Mah10,
  author = {Mahmood, A. and Fatima, I. and Kosar, S. and Ahmed, R. and Malik,
        A.},
  title = {Structural determination of prunusins A and B, new C-alkylated flavonoids
        from Prunus domestica, by 1D and 2D NMR spectroscopy},
  journal = {Magnetic Resonance in Chemistry},
  year = {2010},
  volume = {48},
  pages = {151-154},
  number = {2},
  abstract = {Prunusins A (1) and B (2), the new C-alkylated flavonoids, have been
        isolated from the seed kernels of Prunus domestica. Their structures
        were assigned from H-1 and C-13 nuclear magnetic resonating spectra,
        DEPT and by correlation spectroscopy, HMQC and HMBC experiments.
        3, 5, 7, 4'-Tetrahydroxyflavone (3) and 3, 5, 7-trihydroxy-8, 4'-dimethoxyflavone
        (4) have also been reported from this species. Both compounds (1)
        and (2) showed significant antifungal activity against pathogenic
        fungus Trichophyton simmi.},
  keywords = {nmr 1d/2d nmr prunus domestica rosaceae c-alkylated flavonoids prunusin
        a prunusin b heartwood}
}

@ARTICLE{Mal99,
  author = {Malakooti, Behnam and Subramanian, Sriram},
  title = {Generalized Polynomial Decomposable Multiple Attribute Utility Functions
        for Ranking and Rating Multiple Criteria Discrete Alternatives},
  journal = {Applied Mathematics and Computation },
  year = {1999},
  volume = {106},
  pages = {69-102},
  number = {1}
}

@INPROCEEDINGS{Man08,
  author = {Efrat Manistersky and Raz Lin and Sarit Kraus},
  title = {Understanding How People Design Trading Agents over Time},
  booktitle = {Proceedings of AAMAS'08},
  year = {2008},
  pages = {1593-1596}
}

@INPROCEEDINGS{Mar11,
  author = {Marsa-Maestre, Ivan and Klein, Mark and de la Hoz, Enrique and Lopez-Carmona, Miguel A.},
  title = {Negowiki: A Set of Community Tools for the Consistent Comparison     of Negotiation Approaches},
  booktitle = {Agents in Principle, Agents in Practice},
  year = {2011},
  editor = {Kinny, David and Hsu, JaneYung-jen and Governatori, Guido and Ghose,
        Aditya K.},
  volume = {7047},
  series = {Lecture Notes in Computer Science},
  pages = {424--435},
  address = {Berlin, Heidelberg},
  publisher = {Springer-Verlag},
  acmid = {2177735},
  doi = {10.1007/978-3-642-25044-6\_34},
  isbn = {978-3-642-25043-9},
  location = {Wollongong, Australia},
  numpages = {12},
  url = {http://dx.doi.org/10.1007/978-3-642-25044-6\_34}
}

@Article{Mar13,
  author   = {Ivan Marsa-Maestre and Mark Klein and Catholijn M. Jonker and Reyhan Aydo{\u{g}}an},
  title    = {From problems to protocols: Towards a negotiation handbook},
  journal  = {Decision Support Systems},
  year     = {2013},
  abstract = {Abstract Automated negotiation protocols represent a potentially powerful
        tool for problem solving in decision support systems involving participants
        with conflicting interests. However, the effectiveness of negotiation
        approaches depends greatly on the negotiation problem under consideration.
        Since there is no one negotiation protocol that clearly outperforms
        all others in all scenarios, we need to be able to decide which protocol
        is most suited for each particular problem. The goal of our work
        is to meet this challenge by defining a negotiation handbook, that
        is, a collection of design rules which allow us, given a particular
        negotiation problem, to choose the most appropriate protocol to address
        it. This paper describes our progress towards this goal, including
        a tool for generating a wide range of negotiation scenarios, a set
        of high-level metrics for characterizing how negotiation scenarios
        differ, a testbed environment for evaluating protocol performance
        with different scenarios, and a community repository which allows
        us to systematically record and analyze protocol performance data.
        },
  doi      = {http://dx.doi.org/10.1016/j.dss.2013.05.019},
  issn     = {0167-9236},
  keywords = {Scenario metrics},
  url      = {http://www.sciencedirect.com/science/article/pii/S016792361300167X},
}

@INPROCEEDINGS{Mar09,
  author = {Marsa-Maestre, Ivan and Lopez-Carmona, Miguel A. and Velasco, Juan R. and Ito, Takayuki and Klein, Mark and Fujita, Katsuhide},
 title = {Balancing Utility and Deal Probability for Auction-based Negotiations in Highly Nonlinear Utility Spaces},
  booktitle = {Proceedings of the 21st international joint conference on artifical intelligence},
   series = {IJCAI'09},
  year = {2009},
  pages = {214--219},
   location = {Pasadena, California, USA},
  organization = {Morgan Kaufmann Publishers Inc.}
}

@BOOK{Mas02,
  title = {Chebyshev Polynomials},
  publisher = {Taylor \& Francis},
  year = {2002},
  author = {Mason, John C. and Handscomb, David C.},
  isbn = {9780849303555},
  lccn = {2002073578},
  owner = {Mark},
  timestamp = {2014.02.18},
  url = {http://books.google.nl/books?id=8FHf0P3to0UC}
}

@INPROCEEDINGS{Mas13,
  author = {Masvoula, Marisa},
  title = {Forecasting Negotiation Counterpart's Offers: A Focus on Session-long Learning Agents},
  booktitle = {COGNITIVE 2013, The Fifth International Conference on Advanced Cognitive Technologies and Applications},
  year = {2013},
  pages = {71--76},
  owner = {Mark},
  timestamp = {2013.06.08}
}

@INCOLLECTION{Mas11,
  author = {Masvoula, Marisa and Halatsis, Constantine and Martakos, Drakoulis},
  title = {Predictive Automated Negotiators Employing Risk-Seeking and Risk-Averse Strategies},
  booktitle = {Engineering Applications of Neural Networks},
  publisher = {Springer Boston},
  year = {2011},
  editor = {Iliadis, Lazaros and Jayne, Chrisina},
  volume = {363},
  series = {IFIP Advances in Information and Communication Technology},
  pages = {325-334},
  affiliation = {Department of Informatics and Telecommunications, National and Kapodistrian
        University of Athens, University Campus, Athens, 15771 Greece},
  isbn = {978-3-642-23956-4},
  keyword = {Computer Science},
  owner = {Mark},
  timestamp = {2013.02.08}
}

@inproceedings{Mas10,
  author = {Masvoula, Marisa and Kanellis, Panagiotis and Martakos, Drakoulis},
  title = {A Review of Learning Methods Enhanced in Strategies of Negotiating Agents},
  booktitle={Proceedings of the 12th International Conference on Enterprise Information Systems},
  year = {2010},
  pages = {212--219},
  owner = {Mark},
  timestamp = {2013.05.26}
}

@INPROCEEDINGS{Mat98,
  author = {Matos, Noyda and Sierra, Carles and Jennings, Nicholas R.},
  title = {Determining successful negotiation strategies: an evolutionary approach},
  booktitle = {Proceedings International Conference on Multi Agent Systems},
  year = {1998},
  pages = {182-189},
  abstract = {To be successful in open, multi-agent environments, autonomous agents
        must be capable of adapting their negotiation strategies and tactics
        to their prevailing circumstances. To this end, we present an empirical
        study showing the relative success of different strategies against
        different types of opponent in different environments. In particular
        we adopt an evolutionary approach in which strategies and tactics
        correspond to the genetic material in a genetic algorithm. We conduct
        a series of experiments to determine the most successful strategies
        and to see how and when these strategies evolve depending on the
        context and negotiation stance of the agent's opponent},
  doi = {10.1109/ICMAS.1998.699048},
  keywords = {cooperative systems;genetic algorithms;software agents;autonomous
        agents;evolutionary approach;genetic algorithm;open multi-agent environments;successful
        negotiation strategies determination;Artificial intelligence;Conducting
        materials;Councils;Educational institutions;Encoding;Genetic algorithms;Multiagent
        systems;Performance evaluation;Tail}
}

@CONFERENCE{Maz12,
  author = {Mazliah, Y. and Gal, Y.},
  title = {Coordination in Multi-Player Human-Computer Groups},
  booktitle = {Proc. of the First Human-Agent Interaction Design and Models Workshop
        (HAIDM)},
  year = {2005}
}

@ARTICLE{McKelvey1992,
  author = {R.D. McKelvey and T.R. Palfrey},
  title = {An Experimental Study of the Centipede Game},
  journal = {Econometrica},
  year = {1992},
  volume = {60},
  pages = {803-836},
  number = {4}
}

@ARTICLE{McTea93,
  author = {McTear, Michael F.},
  title = {User modelling for adaptive computer systems: a survey of recent
        developments},
  journal = {Artificial Intelligence Review},
  year = {1993},
  volume = {7},
  pages = {157-184},
  number = {3-4},
  doi = {10.1007/BF00849553},
  issn = {0269-2821},
  keywords = {adaptive system; user models; intelligent interfaces; knowledge representation;
        user modelling shells},
  language = {English},
  publisher = {Kluwer Academic Publishers},
  url = {http://dx.doi.org/10.1007/BF00849553}
}

@MASTERSTHESIS{Mel07,
  author = {Meloche, P.},
  title = {Experimental investigation of quasi-Newton approaches to a learning
        problem in electronic negotiation},
  school = {University of Waterloo},
  year = {2007},
  owner = {Mark},
  timestamp = {2013.02.12}
}

@ARTICLE{Mye83,
  author = {Roger B Myerson and Mark A Satterthwaite},
  title = {Efficient mechanisms for bilateral trading },
  journal = {Journal of Economic Theory },
  year = {1983},
  volume = {29},
  pages = {265 - 281},
  number = {2},
  abstract = {We consider bargaining problems between one buyer and one seller for
        a single object. The seller's valuation and the buyer's valuation
        for the object are assumed to be independent random variables, and
        each individual's valuation is unknown to the other. We characterize
        the set of allocation mechanisms that are Bayesian incentive compatible
        and individually rational, and show the general impossibility of
        ex post efficient mechanisms without outside subsidies. For a wide
        class of problems we show how to compute mechanisms that maximize
        expected total gains from trade, and mechanisms that can maximize
        a broker's expected profit. },
  doi = {http://dx.doi.org/10.1016/0022-0531(83)90048-0},
  issn = {0022-0531},
  url = {http://www.sciencedirect.com/science/article/pii/0022053183900480}
}

@ARTICLE{Mok05,
  author = {Mok, Wilson Wai Ho and Sundarraj, Rangaraja P.},
  title = {Learning algorithms for single-instance electronic negotiations using
        the time-dependent behavioral tactic},
  journal = {ACM Transactions on Internet Technology},
  year = {2005},
  volume = {5},
  pages = {195--230},
  number = {1},
  month = {Feb},
  acmid = {1052941},
  address = {New York, NY, USA},
  doi = {10.1145/1052934.1052941},
  issn = {1533-5399},
  issue_date = {February 2005},
  keywords = {Electronic negotiation, electronic agents, electronic commerce, learning,
        time-dependent tactic.},
  numpages = {36},
  publisher = {ACM},
  url = {http://doi.acm.org/10.1145/1052934.1052941}
}

@BOOK{noitacol,
  title = {Theory of games and economic behavior},
  publisher = {Princeton University Press},
  year = {1953},
  author = {Morgenstern, Oskar and Von Neumann, John},
  abstract = {The nature of the problems investigated and the techniques employed
        in this book necessitate a procedure which in many instances is thoroughly
        mathematical. The mathematical devices used are elementary in the
        sense that no advanced algebra, or calculus, etc., occurs. (With
        two, rather unimportant, exceptions: Part of the discussion of an
        example in 19.7. et sequ. and a remark in A.3.3. make use of some
        simple integrals.) Concepts originating in set theory, linear geometry
        and group theory play an important role, but they are invariably
        taken from the early chapters of those disciplines and are moreover
        analyzed and explained in special expository sections. Nevertheless
        the book is not truly elementary because the mathematical deductions
        are frequently intricate and the logical possibilities are extensively
        exploited. Thus no specific knowledge of any particular body of advanced
        mathematics is required. However, the reader who wants to acquaint
        himself more thoroughly with the subject expounded here, will have
        to familiarize himself with the mathematical way of reasoning definitely
        beyond its routine, primitive phases. The character of the procedures
        will be mostly that of mathematical logics, set theory and functional
        analysis. We have attempted to present the subject in such a form
        that a reader who is moderately versed in mathematics can acquire
        the necessary practice in the course of this study. We hope that
        we have not entirely failed in this endeavour. In accordance with
        this, the presentation is not what it would be in a strictly mathematical
        treatise. All definitions and deductions are considerably broader
        than they would be there. Besides, purely verbal discussions and
        analyses take up a considerable amount of space. We have in particular
        tried to give, whenever possible, a parallel verbal exposition for
        every major mathematical deduction. It is hoped that this procedure
        will elucidate in unmathematical language what the mathematical technique
        signifies-and will also show where it achieves more than can be done
        without it. ?!? In this, as well as in our methodological stand,
        we are trying to follow the best examples of theoretical physics.
        The reader who is not specifically interested in mathematics should
        at first omit those sections of the book which in his judgment are
        too mathematical. We prefer not to give a definite list of them,
        since this judgment must necessarily be subjective. However, those
        sections marked with an asterisk in the table of contents are most
        likely to occur to the average reader inthis connection. At any rate
        he will find that these omissions will little interfere with the
        comprehension of the early parts, although the logical chain may
        in the rigorous sense have suffered an interruption. As he proceeds
        the omissions will gradually assume a more serious character and
        the lacunae in the deduction will become more and more significant.
        The reader is then advised to start again from the beginning since
        the greater familiarity acquired is likely to facilitate a better
        understanding. },
  institution = {I-Revues [http://documents.irevues.inist.fr/dspace-oai/request] (France)},
  location = {http://www.scientificcommons.org/50906158},
  owner = {tim},
  timestamp = {2010.07.15},
  url = {http://hdl.handle.net/2042/28548}
}

@ARTICLE{Mot87,
  author = {Motulsky, Harvey J. and Ransnas, Lennart A.},
  title = {Fitting curves to data using nonlinear regression: a practical and
        nonmathematical review.},
  journal = {The FASEB Journal},
  year = {1987},
  volume = {1},
  pages = {365-74},
  number = {5},
  abstract = {Many types of data are best analyzed by fitting a curve using nonlinear
        regression, and computer programs that perform these calculations
        are readily available. Like every scientific technique, however,
        a nonlinear regression program can produce misleading results when
        used inappropriately. This article reviews the use of nonlinear regression
        in a practical and nonmathematical manner to answer the following
        questions: Why is nonlinear regression superior to linear regression
        of transformed data? How does nonlinear regression differ from polynomial
        regression and cubic spline? How do nonlinear regression programs
        work? What choices must an investigator make before performing nonlinear
        regression? What do the final results mean? How can two sets of data
        or two fits to one set of data be compared? What problems can cause
        the results to be wrong? This review is designed to demystify nonlinear
        regression so that both its power and its limitations will be appreciated.},
  eprint = {http://www.fasebj.org/content/1/5/365.full.pdf+html},
  url = {http://www.fasebj.org/content/1/5/365.abstract}
}

@INPROCEEDINGS{Mud00,
  author = {Mudgal, Chhaya and Vassileva, Julita},
  title = {Bilateral Negotiation with Incomplete and Uncertain Information:
        A Decision-Theoretic Approach Using a Model of the Opponent},
  booktitle = {Proceedings of the 4th International Workshop on Cooperative Information
        Agents IV, The Future of Information Agents in Cyberspace},
  year = {2000},
  series = {CIA '00},
  pages = {107--118},
  address = {London, UK, UK},
  publisher = {Springer-Verlag},
  acmid = {735572},
  isbn = {3-540-67703-8},
  numpages = {12},
  url = {http://dl.acm.org/citation.cfm?id=647785.735572}
}

@ARTICLE{Mur99,
  author = {Murnighan, J Keith and Babcock, Linda and Thompson, Leigh and Pillutla,     Madan},
  title = {The information dilemma in negotiations: Effects of experience, incentives, and integrative potential},
  journal = {International Journal of Conflict Management},
  year = {1999},
  volume = {10},
  pages = {313--339},
  number = {4},
  publisher = {MCB UP Ltd}
}

@ARTICLE{Nad03,
  author = {Nadler, J. and Thompson, L. and van Boven, L.},
  title = {Learning Negotiation Skills: Four Models of Knowledge Creation and
        Transfer},
  journal = {Journal of Management Science},
  year = {2003},
  volume = {49},
  pages = {529-540},
  number = {4}
}

@INCOLLECTION{Nar06,
  author = {Narayanan, Vidya and Jennings, Nicholas R.},
  title = {Learning to Negotiate Optimally in Non-stationary Environments},
  booktitle = {Cooperative Information Agents X},
  publisher = {Springer Berlin Heidelberg},
  year = {2006},
  editor = {Klusch, Matthias and Rovatsos, Michael and Payne, Terry R.},
  volume = {4149},
  series = {Lecture Notes in Computer Science},
  pages = {288-300},
  doi = {10.1007/11839354\_21},
  isbn = {978-3-540-38569-1},
  owner = {Mark},
  timestamp = {2013.06.08},
  url = {http://dx.doi.org/10.1007/11839354\_21}
}

@ARTICLE{Nas50,
  author = {Nash, John F.},
  title = {The Bargaining Problem},
  journal = {Econometrica},
  year = {1950},
  volume = {18},
  pages = {155--162},
  number = {2},
  publisher = {The Econometric Society},
  ISSN = {00129682},
  abstract = {A new treatment is presented of a classical economic problem, one
        which occurs in many forms, as bargaining, bilateral monopoly, etc.
        It may also be regarded as a nonzero-sum two-person game. In this
        treatment a few general assumptions are made concerning the behavior
        of a single individual and of a group of two individuals in certain
        economic environments. From these, the solution (in the sense of
        this paper) of the classical problem may be obtained. In the terms
        of game theory, values are found for the game.},
  citeulike-article-id = {93163},
  citeulike-linkout-0 = {http://dx.doi.org/10.2307/1907266},
  citeulike-linkout-1 = {http://www.jstor.org/stable/1907266},
  doi = {10.2307/1907266},
  keywords = {aarmicro, bargaining, microeconomics, tartumicro},
  owner = {tim},
  posted-at = {2005-02-11 11:33:55},
  priority = {5},
  timestamp = {2010.03.19},
  url = {http://dx.doi.org/10.2307/1907266}
}

@MISC{Ngu03,
  author = {Nguyen, Thuc Duong and Jennings, Nicholas R.},
  title = {Concurrent bilateral negotiation in agent systems},
  year = {2003},
  isbn = {1529-4188 },
  pages = {844-849}
}

@INPROCEEDINGS{Ngu04,
  author = {Nguyen, Thuc Duong and Jennings, Nicholas R.},
  title = {Coordinating Multiple Concurrent Negotiations},
  booktitle = {Proceedings of the Third International Joint Conference on Autonomous
        Agents and Multiagent Systems},
        volume = {3},
  year = {2004},
  series = {AAMAS '04},
  pages = {1064--1071},
  address = {Washington, DC, USA},
  publisher = {IEEE Computer Society},
  acmid = {1018875},
  doi = {10.1109/AAMAS.2004.94},
  isbn = {1-58113-864-4},
  location = {New York, NY, USA},
  numpages = {8},
  url = {http://dx.doi.org/10.1109/AAMAS.2004.94}
}

@INCOLLECTION{Nie09,
  author = {Christoph Niemann and Florian Lang},
  title = {Assess Your Opponent: A Bayesian Process for Preference Observation
        in Multi-attribute Negotiations},
  booktitle = {Advances in Agent-Based Complex Automated Negotiations},
  publisher = {Springer Berlin Heidelberg},
  year = {2009},
  editor = {Ito, Takayuki and Zhang, Minjie and Robu, Valentin and Fatima, Shaheen
        and Matsuo, Tokuro},
  volume = {233},
  series = {Studies in Computational Intelligence},
  pages = {119--137},
  isbn = {978-3-642-03189-2},
  keyword = {Engineering},
  owner = {Mark},
  timestamp = {2013.02.08}
}

@BOOK{nis07,
  title = {Algorithmic game theory},
  publisher = {Cambridge University Press},
  year = {2007},
  author = {Nisan, N. and Roughgarden, T. and Tardos, E. and Vazirani, V.V.}
}

@ARTICLE{Niu10,
  author = {Niu, Jinzhong and Cai, Kai and Parsons, Simon and McBurney, Peter
        and Gerding, Enrico H.},
  title = {What the 2007 TAC Market Design Game tells us about effective auction mechanisms},
  journal = {Autonomous Agents and Multi-Agent Systems},
  year = {2010},
  volume = {21},
  pages = {172-203},
  doi = {10.1007/s10458-009-9110-0},
  issn = {1387-2532},
  issue = {2},
  keywords = {Double auction; Mechanism design; Trading agent competition},
  language = {English},
  owner = {Mark},
  publisher = {Springer US},
  timestamp = {2013.02.11},
  url = {http://dx.doi.org/10.1007/s10458-009-9110-0}
}

@INPROCEEDINGS{Noh11,
  author = {Noh, H. and Ozonat, K. and Singhal, S. and Yang, Y.},
  title = {A multi-choice offer strategy for bilateral multi-issue negotiations
        using modified DWM learning},
  booktitle = {Proceedings of the 13th International Conference on Electronic Commerce},
  year = {2011},
  pages = {2--5},
  owner = {Mark},
  timestamp = {2013.01.27}
}

@INPROCEEDINGS{Oli06,
  author = {R{\^o}mulo Silva de Oliveira and Herman Gomes and Alan Silva and
        Ig Ibert Bittencourt and Evandro de Barros Costa},
  title = {A Multi-Agent Based Framework for Supporting Learning in Adaptive
        Automated Negotiation},
  booktitle = {ICEIS (4)},
  year = {2006},
  pages = {153-158},
  bibsource = {DBLP, http://dblp.uni-trier.de},
  owner = {Mark},
  timestamp = {2013.02.08}
}

@INCOLLECTION{Oli05,
  author = {Oliver, Jim R.},
  title = {On Learning Negotiation Strategies by Artificial Adaptive Agents
        in Environments of Incomplete Information},
  booktitle = {Formal Modelling in Electronic Commerce},
  publisher = {Springer Berlin Heidelberg},
  year = {2005},
  editor = {Kimbrough, Steven O. and Wu, D.J.},
  series = {International Handbooks on Information Systems},
  pages = {445-461},
  affiliation = {INSEAD France},
  isbn = {978-3-540-26989-2},
  keyword = {Business and Economics},
  owner = {Mark},
  timestamp = {2013.02.08}
}

@ARTICLE{Oli96,
  author = {Oliver, Jim R.},
  title = {A machine-learning approach to automated negotiation and prospects
        for electronic commerce},
  journal = {Journal of Management Information Systems},
  year = {1996},
  volume = {13},
  pages = {83--112},
  month = {Dec},
  acmid = {1189554},
  address = {Armonk, NY, USA},
  issn = {0742-1222},
  issue = {3},
  numpages = {30},
  owner = {Mark},
  publisher = {M. E. Sharpe, Inc.},
  timestamp = {2013.02.08}
}

@INPROCEEDINGS{Oli96Commerce,
  author = {Oliver, Jim R.},
  title = {On Artificial Agents for Negotiation in Electronic Commerce},
  booktitle = {Proceedings of the Twenty-Ninth Hawaii International Conference on System Sciences},
  year = {1996},
  volume = {4},
  pages = {337-346 vol.4},
  abstract = {A well-established body of research consistently shows that people
        involved in multiple-issue negotiations frequently select pareto-inferior
        agreements that leave money on the table. Using an evolutionary computation
        approach, we show how simple, boundedly rational, artificial adaptive
        agents can learn to perform similarly to humans at stylized negotiations.
        Furthermore, there is the promise that these agents can be integrated
        into practicable electronic commerce systems which would not only
        leave less money on the table, but would enable new types of transactions
        to be negotiated cost effectively},
  doi = {10.1109/HICSS.1996.495355},
  keywords = {commerce;decision support systems;knowledge based systems;learning
        (artificial intelligence);negotiation support systems;software agents;transaction
        processing;artificial adaptive agents;artificial agents;boundedly
        rational adaptive agents;electronic commerce;humans;multiple-issue
        negotiations;pareto-inferior agreements;stylized negotiations;transactions;Autonomous
        agents;Costs;Electronic commerce;Evolutionary computation;Game theory;Humans;Machine
        learning;Robustness}
}

@ARTICLE{Opr02,
  author = {Oprea, Mihaela},
  title = {An adaptive negotiation model for agent-based electronic commerce},
  journal = {Studies in Informatics and Control},
  year = {2002},
  volume = {11},
  pages = {271--279},
  number = {3},
  owner = {README - cites bekeken},
  publisher = {INFORMATICS AND CONTROL PUBLICATIONS},
  timestamp = {2011.06.14}
}

@INPROCEEDINGS{Ore10,
  author = {Oren, N. and Norman, T.J.},
  title = {Arguing Using Opponent Models},
  booktitle = {Argumentation in Multi-Agent Systems: 6th International Workshop,
        ArgMAS 2009, Budapest, Hungary, May 12, 2009. Revised Selected and
        Invited Papers},
  year = {2010},
  volume = {6057},
  pages = {160},
  organization = {Springer-Verlag New York Inc},
  owner = {Mark},
  timestamp = {2012.07.18}
}

@BOOK{Osb94,
  title = {A Course in Game Theory},
  publisher = {The MIT Press},
  year = {1994},
  author = {Osborne, Martin J. and Rubinstein, Ariel},
  edition = {1st},
  abstract = {A Course in Game Theory presents the main ideas of game theory at
        a level suitable for graduate students and advanced undergraduates,
        emphasizing the theory's foundations and interpretations of its basic
        concepts. The authors provide precise definitions and full proofs
        of results, sacrificing generalities and limiting the scope of the
        material in order to do so. The text is organized in four parts:
        strategic games, extensive games with perfect information, extensive
        games with imperfect information, and coalitional games. It includes
        over 100 exercises.},
  keywords = {game theory; strategic games; extensive games; coalitional games},
  url = {http://EconPapers.repec.org/RePEc:mtp:titles:0262650401}
}

@BOOK{Osb90,
  title = {Bargaining and Markets (Economic Theory, Econometrics, and Mathematical
        Economics)},
  publisher = {Academic Press},
  year = {1990},
  author = {Osborne, Martin J. and Rubinstein, Ariel},
  month = {Apr},
  abstract = {{The formal theory of bargaining originated with John Nash's work
        in the early 1950s. This book discusses two recent developments in
        this theory. The first uses the tool of extensive games to construct
        theories of bargaining in which time is modeled explicitly. The second
        applies the theory of bargaining to the study of decentralized markets.
        Rather than surveying the field, the authors present a select number
        of models, each of which illustrates a key point. In addition, they
        give detailed proofs throughout the book.<br><br>Key Features<br>*
        Uses a small number of models, rather than a survey of the field,
        to illustrate key points<br>* Detailed proofs are given as explanations
        for the models <br>* Text has been class-tested in a semester-long
        graduate course}},
  citeulike-article-id = {453337},
  citeulike-linkout-0 = {http://www.amazon.ca/exec/obidos/redirect?tag=citeulike09-20\&amp;path=ASIN/0125286325},
  citeulike-linkout-1 = {http://www.amazon.de/exec/obidos/redirect?tag=citeulike01-21\&amp;path=ASIN/0125286325},
  citeulike-linkout-2 = {http://www.amazon.fr/exec/obidos/redirect?tag=citeulike06-21\&amp;path=ASIN/0125286325},
  citeulike-linkout-3 = {http://www.amazon.jp/exec/obidos/ASIN/0125286325},
  citeulike-linkout-4 = {http://www.amazon.co.uk/exec/obidos/ASIN/0125286325/citeulike00-21},
  citeulike-linkout-5 = {http://www.amazon.com/exec/obidos/redirect?tag=citeulike07-20\&path=ASIN/0125286325},
  citeulike-linkout-6 = {http://www.worldcat.org/isbn/0125286325},
  citeulike-linkout-7 = {http://books.google.com/books?vid=ISBN0125286325},
  citeulike-linkout-8 = {http://www.amazon.com/gp/search?keywords=0125286325\&index=books\&linkCode=qs},
  citeulike-linkout-9 = {http://www.librarything.com/isbn/0125286325},
  day = {28},
  howpublished = {Paperback},
  isbn = {0125286325},
  keywords = {book, equilibrium, evol-game, game, game-theory, market},
  owner = {tim},
  posted-at = {2009-09-28 11:51:28},
  priority = {2},
  timestamp = {2010.03.19},
  url = {http://www.worldcat.org/isbn/0125286325}
}

@INPROCEEDINGS{Osh09,
  author = {Oshrat, Yinon and Lin, Raz and Kraus, Sarit},
  title = {Facing the challenge of human-agent negotiations via effective general
        opponent modeling},
  booktitle = {Proceedings of The 8th International Conference on Autonomous Agents
        and Multiagent Systems},
         series = {AAMAS '09},
          isbn = {978-0-9817381-6-1},
           location = {Budapest, Hungary},
  year = {2009},
  volume = {1},
  pages = {377--384},
  publisher = {International Foundation for Autonomous Agents and Multiagent Systems},
   address = {Richland, SC},
  owner = {---},
  timestamp = {2011.06.14}
}

@INCOLLECTION{Ozo10,
  author = {Ozonat, Kivanc and Singhal, Sharad},
  title = {Design of Negotiation Agents Based on Behavior Models},
  booktitle = {Web Information Systems Engineering - WISE 2010},
  publisher = {Springer Berlin Heidelberg},
  year = {2010},
  editor = {Chen, Lei and Triantafillou, Peter and Suel, Torsten},
  volume = {6488},
  series = {Lecture Notes in Computer Science},
  pages = {308-321},
  doi = {10.1007/978-3-642-17616-6\_28},
  isbn = {978-3-642-17615-9},
  owner = {Mark},
  timestamp = {2013.06.17},
  url = {http://dx.doi.org/10.1007/978-3-642-17616-6\_28}
}

@incollection{Pap11,
year={2011},
isbn={978-3-642-21500-1},
booktitle={Advances in Computational Intelligence},
volume={6691},
series={Lecture Notes in Computer Science},
editor={Cabestany, Joan and Rojas, Ignacio and Joya, Gonzalo},
doi={10.1007/978-3-642-21501-8_15},
title={Multi-modal Opponent Behaviour Prognosis in E-Negotiations},
url={http://dx.doi.org/10.1007/978-3-642-21501-8_15},
publisher={Springer Berlin Heidelberg},
keywords={Negotiating Agents; opponent behaviour prediction; MLP & RBF Neural Networks; Polynomial Approximators},
  author = {Papaioannou, Ioannis V. and Roussaki, Ioanna G. and Anagnostou, Miltiades E.},
pages={113-123},
language={English}
}


@incollection{Pap09,
  author = {Papaioannou, Ioannis V. and Roussaki, Ioanna G. and Anagnostou, Miltiades E.},
  title = {A Survey on Neural Networks in Automated Negotiations},
    editor = {Rabu\~nal, Juan R. and Dorado, Julian and Pazos, Alejandro},
  booktitle = {Encyclopedia of Artificial Intelligence},
    publisher = {IGI Global},
  year = {2009},
  pages = {1524--1529},
  owner = {Mark},
  timestamp = {2012.04.09}
}

@ARTICLE{Pap08,
  author = {Papaioannou, Ioannis V. and Roussaki, Ioanna G. and Anagnostou, Miltiades E.},
  title = {Neural networks against genetic algorithms for negotiating agent
        behaviour prediction},
  journal = {Web Intelligence and Agent Systems},
  year = {2008},
  month = {Apr},
  volume = {6},
  issn = {1570-1263},
  doi = {10.3233/WIA-2008-0138},
  pages = {217--233},
  number = {2},
  owner = {Mark},
  publisher = {IOS Press},
  address = {Amsterdam, The Netherlands},
  timestamp = {2012.04.17}
}

@INPROCEEDINGS{Pap06,
  author = {Papaioannou, Ioannis V. and Roussaki, Ioanna G. and Anagnostou, Miltiades
        E.},
  title = {Comparing the Performance of MLP and RBF Neural Networks Employed
        by Negotiating Intelligent Agents},
  booktitle = {Proceedings of the IEEE/WIC/ACM international conference on Intelligent
        Agent Technology},
  year = {2006},
  series = {IAT '06},
  pages = {602--612},
  address = {Washington, DC, USA},
  publisher = {IEEE Computer Society},
  acmid = {1194610},
  isbn = {0-7695-2748-5},
  numpages = {11},
  owner = {Mark},
  timestamp = {2013.02.08}
}

@ARTICLE{par05,
  author = {Parkes, D.C. and Kalagnanam, J.},
  title = {Models for iterative multiattribute procurement auctions},
  journal = {Management Science},
  year = {2005},
  volume = {51},
  pages = {435-451},
  number = {3}
}

@article{Par02,
year={2002},
issn={1387-2532},
journal={Autonomous Agents and Multi-Agent Systems},
volume={5},
number={3},
doi={10.1023/A:1015575522401},
title={Game Theory and Decision Theory in Multi-Agent Systems},
url={http://dx.doi.org/10.1023/A%3A1015575522401},
publisher={Kluwer Academic Publishers},
keywords={game theory; decision theory},
author={Parsons, Simon and Wooldridge, Michael J.},
pages={243-254},
language={English}
}


@PROCEEDINGS{Pau01,
  title = {Bilateral Negotiation for Agent-Mediated Electronic Commerce},
  year = {2001},
  address = {London, UK},
  publisher = {Springer-Verlag},
  author = {Paula, Gustavo de and Ramos, Francisco and Ramalho, Geber},
  booktitle = {Agent-Mediated Electronic Commerce III, Current Issues in Agent-Based
        Electronic Commerce Systems (includes revised papers from AMEC 2000
        Workshop)},
  isbn = {3-540-41749-4},
  owner = {tim},
  pages = {1--14},
  timestamp = {2010.07.23}
}

@PHDTHESIS{Pom12,
  author = {Alina Pommeranz},
  title = {Designing Human-Centered Systems for Reflective Decision Making},
  school = {Delft University of Technology},
  year = {2012},
  type = {Dissertation},
  isbn = {978-94-61913-65-4}
}

@INPROCEEDINGS{Pom08,
  author = {Pommeranz, Alina and Broekens, Joost and Visser, Wietske and Brinkman, Willem-Paul and Wiggers, Pascal and Jonker, Catholijn M.},
  title = {Multi-angle View on Preference Elicitation for Negotiation Support Systems},
  booktitle = {Proceedings of the 1st International Working Conference on Human Factors and Computational Models in Negotiation},
  year = {2009},
  series = {HuCom '08},
  pages = {19--26},
  address = {New York, NY, USA},
  publisher = {ACM},
  acmid = {1609173},
  doi = {10.1145/1609170.1609173},
  isbn = {978-90-813811-1-6},
  keywords = {affective scoring, lexicographic ordering, preference elicitation,
        recommender systems},
  location = {Delft, The Netherlands},
  numpages = {8},
  url = {http://doi.acm.org/10.1145/1609170.1609173}
}

@ARTICLE{Pom12values,
  author = {Pommeranz, Alina and Detweiler, Christian and Wiggers, Pascal and Jonker, Catholijn M.},
  title = {Elicitation of situated values: need for tools to help stakeholders and designers to reflect and communicate},
  journal = {Ethics and Information Technology},
  year = {2012},
  volume = {14},
  pages = {285-303},
  number = {4},
  doi = {10.1007/s10676-011-9282-6},
  issn = {1388-1957},
  keywords = {Value elicitation; Self-reflection; Situated values; Value sensitive
        design; Design methods},
  language = {English},
  publisher = {Springer Netherlands},
  url = {http://dx.doi.org/10.1007/s10676-011-9282-6}
}

@ARTICLE{Pra64,
  author = {Pratt, John W},
  title = {Risk Aversion in the Small and in the Large},
  journal = {Econometrica: Journal of the Econometric Society},
  year = {1964},
  volume = {32},
  pages = {122--136},
  publisher = {JSTOR}
}

@BOOK{Pru81,
  title = {Negotiation Behavior},
  publisher = {Academic Press},
  year = {1981},
  author = {Dean G. Pruitt},
  owner = {tim},
  timestamp = {2011.05.31}
}

@ARTICLE{Rah11,
  author = {Rahman, Samir Abdel and Bahgat, Reem and Farag, George M.},
  title = {Order Statistics Bayesian-Mining Agent Modelling for Automated Negotiation},
  journal = {Informatica: An International Journal of Computing and Informatics},
  year = {2011},
  volume = {35},
  pages = {123--137},
  number = {1},
  owner = {Mark},
  publisher = {Slovene Society Informatika, Vozarski pot 12 1000 Ljubljana, Slovenia},
  timestamp = {2013.02.02}
}

@article{Rah02,
 author = {Rahwan, Iyad and Kowalczyk, Ryszard and Pham, Ha Hai},
 title = {Intelligent Agents for Automated One-to-many e-Commerce Negotiation},
 journal = {Australian Computer Science Communications},
 issue_date = {January-February 2002},
 volume = {24},
 number = {1},
 month = {Jan},
 year = {2002},
 pages = {197--204},
 numpages = {8},
 url = {http://dx.doi.org/10.1145/563857.563824},
 doi = {10.1145/563857.563824},
 acmid = {563824},
 publisher = {IEEE Computer Society Press},
 address = {Los Alamitos, CA, USA},
 keywords = {automated negotiation, electronic commerce, multi-agent systems},
} 


@ARTICLE{Rah03,
  author = {Rahwan, Iyad and Ramchurn, Sarvapalic and Jennings, Nicholas R. and
        McBurney, Peter and Parsons, Simon and Sonenberg, Liz},
  title = {Argumentation-based negotiation},
  journal = {The Knowledge Engineering Review},
  year = {2003},
  volume = {18},
  pages = {343-375},
  number = {04},
  abstract = {Negotiation is essential in settings where autonomous agents have
        conflicting interests and a desire to cooperate. For this reason,
        mechanisms in which agents exchange potential agreements according
        to various rules of interaction have become very popular in recent
        years as evident, for example, in the auction and mechanism design
        community. However, a growing body of research is now emerging which
        points out limitations in such mechanisms and advocates the idea
        that agents can increase the likelihood and quality of an agreement
        by exchanging arguments which influence each other; states. This
        community further argues that argument exchange is sometimes essential
        when various assumptions about agent rationality cannot be satisfied.
        To this end, in this article, we identify the main research motivations
        and ambitions behind work in the field. We then provide a conceptual
        framework through which we outline the core elements and features
        required by agents engaged in argumentation-based negotiation, as
        well as the environment that hosts these agents. For each of these
        elements, we survey and evaluate existing proposed techniques in
        the literature and highlight the major challenges that need to be
        addressed if argument-based negotiation research is to reach its
        full potential. },
  doi = {DOI:10.1017/S0269888904000098},
  eprint = {http://journals.cambridge.org/article\_S0269888904000098},
  owner = {tim},
  timestamp = {2010.03.29},
  url = {http://journals.cambridge.org/article\_S0269888904000098}
}

@ARTICLE{Rah07,
  author = {Iyad Rahwan and Liz Sonenberg and Nicholas R. Jennings and Peter
        McBurney},
  title = {STRATUM: A Methodology for Designing Heuristic Agent Negotiation
        Strategies},
  journal = {Applied Artificial Intelligence},
  year = {2007},
  volume = {21},
  pages = {489-527},
  number = {6},
  bibsource = {DBLP, http://dblp.uni-trier.de},
  ee = {http://dx.doi.org/10.1080/08839510701408971},
  owner = {tim},
  timestamp = {2011.03.08}
}

@article{Rai53,
  title={Arbitration schemes for generalized two-person games},
  author={Raiffa, Howard},
  journal={Annals of Mathematics Studies},
  volume={28},
  pages={361--387},
  year={1953},
  publisher={Princeton University Press Princeton, NJ}
}

@BOOK{Rai82,
  title = {The art and science of negotiation: How to resolve conflicts and
        get the best out of bargaining},
  publisher = {Harvard University Press},
  year = {1982},
  author = {Raiffa, Howard},
  address = {Cambridge, MA}
}

@BOOK{Rai03,
  title = {Negotiation Analysis: The Science and Art of Collaborative Decision
        Making},
  publisher = {Harvard University Press},
  year = {2003},
  author = {Raiffa, Howard and Richardson, John and Metcalfe, David}
}

@ARTICLE{Ram07,
  author = {Sarvapali D. Ramchurn and Carles Sierra and Llu\'{i}s Godo and Nicholas
        R. Jennings},
  title = {Negotiating using rewards},
  journal = {Artificial Intelligence},
  year = {2007},
  volume = {171},
  pages = {805 - 837},
  number = {10-15},
  note = {Argumentation in Artificial Intelligence},
  abstract = {Negotiation is a fundamental interaction mechanism in multi-agent
        systems because it allows self-interested agents to come to mutually
        beneficial agreements and partition resources efficiently and effectively.
        Now, in many situations, the agents need to negotiate with one another
        many times and so developing strategies that are effective over repeated
        interactions is an important challenge. Against this background,
        a growing body of work has examined the use of Persuasive Negotiation
        (PN), which involves negotiating using rhetorical arguments (such
        as threats, rewards, or appeals), in trying to convince an opponent
        to accept a given offer. Such mechanisms are especially suited to
        repeated encounters because they allow agents to influence the outcomes
        of future negotiations, while negotiating a deal in the present one,
        with the aim of producing results that are beneficial to both parties.
        To this end, in this paper, we develop a comprehensive PN mechanism
        for repeated interactions that makes use of rewards that can be asked
        for or given to. Our mechanism consists of two parts. First, a novel
        protocol that structures the interaction by capturing the commitments
        that agents incur when using rewards. Second, a new reward generation
        algorithm that constructs promises of rewards in future interactions
        as a means of permitting agents to reach better agreements, in a
        shorter time, in the present encounter. We then go on to develop
        a specific negotiation tactic, based on this reward generation algorithm,
        and show that it can achieve significantly better outcomes than existing
        benchmark tactics that do not use such inducements. Specifically,
        we show, via empirical evaluation in a Multi-Move Prisoners' Dilemma
        setting, that our tactic can lead to a 26% improvement in the utility
        of deals that are made and that 21 times fewer messages need to be
        exchanged in order to achieve this.},
  doi = {DOI: 10.1016/j.artint.2007.04.014},
  issn = {0004-3702},
  keywords = {Persuasive negotiation},
  owner = {tim},
  timestamp = {2011.03.08},
  url = {http://www.sciencedirect.com/science/article/B6TYF-4NNYJBM-1/2/1094bbecc8f8f04ae1d2ee63d4a14ea3}
}

@INPROCEEDINGS{Ram11,
  author = {Ramezani, F. and Ghasem-Aghaee, N. and Kazemifard, M.},
  title = {Modeling of emotional-social negotiator agents},
  booktitle = {11th International Conference on Intelligent Systems Design and Applications (ISDA)},
  year = {2011},
  pages = {42-46},
  doi = {10.1109/ISDA.2011.6121628},
  issn = {2164-7143},
  keywords = {multi-agent systems;emotional-social negotiator agents;individual
        utility;multiagent system;social intelligence;Autonomous agents;Bayesian
        methods;Computer architecture;Decision making;Intelligent systems;Multiagent
        systems;BDI architecture;Emotion;Multi agent systems;Negotiation;Social
        intelligence}
}

@ARTICLE{Rau06,
  author = {Hsin Rau and Mou-Hsing Tsai and Chao-Wen Chen and Wei-Jung Shiang},
  title = {Learning-based automated negotiation between shipper and forwarder},
  journal = {Computers \& industrial engineering},
  year = {2006},
  volume = {51},
  pages = {464--481},
  number = {3},
  doi = {http://dx.doi.org/10.1016/j.cie.2006.08.008},
  issn = {0360-8352},
  keywords = {Negotiation},
  owner = {Mark},
  publisher = {Elsevier},
  timestamp = {2013.01.25},
  url = {http://www.sciencedirect.com/science/article/pii/S0360835206001070}
}

@INCOLLECTION{Ren07,
  author = {Ren, Fenghui and Zhang, Minjie},
  title = {Predicting Partners' Behaviors in Negotiation by Using Regression
        Analysis},
  booktitle = {Knowledge Science, Engineering and Management},
  publisher = {Springer Berlin Heidelberg},
  year = {2007},
  editor = {Zhang, Zili and Siekmann, J\"{o}rg},
  volume = {4798},
  series = {Lecture Notes in Computer Science},
  pages = {165-176},
  doi = {10.1007/978-3-540-76719-0\_19},
  isbn = {978-3-540-76718-3},
  owner = {Mark},
  timestamp = {2013.06.09},
  url = {http://dx.doi.org/10.1007/978-3-540-76719-0\_19}
}

@ARTICLE{Ren02,
  author = {Ren, Zhaomin and Anumba, Chimay J.},
  title = {Learning in multi-agent systems: a case study of construction claims
        negotiation},
        issn = "1474-0346",
doi = "http://dx.doi.org/10.1016/S1474-0346(03)00015-6",
  journal = {Advanced Engineering Informatics},
  year = {2002},
  volume = {16},
  pages = {265--275},
  number = {4},
  owner = {Mark},
  publisher = {Elsevier},
  timestamp = {2013.01.25}
}

@MASTERSTHESIS{Ren11,
  author = {Rens, Thomas Pieter},
  title = {A Multi Party Negotiation Game for Improving Crisis Management Decision      Making and Conflict Resolving},
  school = {Technical University of Delft},
  year = {2011}
}

@CONFERENCE{Res04,
  author = {Angelo Restificar and Peter Haddawy},
  title = {Inferring Implicit Preferences from Negotiation Actions},
  booktitle = {International Symposium on Artificial Intelligence and Mathematics},
  year = {2004},
  address = {Fort Lauderdale, Florida, USA},
  month = {Jan},
  abstract = {In this paper we propose to model a negotiator's decision-making behavior,
        expressed as preferences between an offer/counter-offer gamble and
        a certain offer, by learning from implicit choices that can be inferred
        from observed negotiation actions. The agent's actions in a negotiation
        sequence provide information about his preferences and risk-taking
        behavior. We show how offers and counter-offers in negotiation can
        be transformed into gamble questions providing a basis for inferring
        implicit preferences. Finally, we present the results of experiments
        and evaluation we have undertaken.},
  attachments = {http://iist.unu.edu/sites/iist.unu.edu/files/biblio/haddawy-pub-42.pdf},
  owner = {Mark},
  timestamp = {2013.02.17}
}

@ARTICLE{Rich11eta,
  author = {Richardson, John T.E.},
  title = {Eta squared and partial eta squared as measures of effect size in educational research},
  journal = {Educational Research Review},
  year = {2011},
  volume = {6},
  pages = {135--147},
  number = {2},
  publisher = {Elsevier}
}

@INCOLLECTION{Riemsdijk12,
  author = {Riemsdijk, M.Birna and Jonker, Catholijn M. and Rens, Thomas and Wang,
        Zhiyong},
  title = {Negotiation Game for Improving Decision Making in Self-managing Teams},
  booktitle = {Modern Advances in Intelligent Systems and Tools},
  publisher = {Springer Berlin Heidelberg},
  year = {2012},
  editor = {Ding, Wei and Jiang, He and Ali, Moonis and Li, Mingchu},
  volume = {431},
  series = {Studies in Computational Intelligence},
  pages = {63-68},
  doi = {10.1007/978-3-642-30732-4\_8},
  isbn = {978-3-642-30731-7},
  url = {http://dx.doi.org/10.1007/978-3-642-30732-4\_8}
}

@INPROCEEDINGS{Rob90,
  author = {Robinson, William N.},
  title = {Negotiation behavior during requirement specification},
  booktitle = {Proceedings of the 12th International Conference on Software Engineering},
  year = {1990},
  month={Mar}, 
  pages = {268-276},
  abstract = {Negotiation is part of specification; during specification acquisition,
        users negotiate among themselves and with analysts. During specification
        design, designers negotiate among themselves and with a project leader.
        The author reports on work concerned with multiagent specification
        design. He describes how various agents, often with conflicting goals,
        can resolve their differences, integrate their results, and produce
        a unified specification. Such bargaining behavior is both ubiquitous
        in complex specification and unrepresented by current methods. Automated
        means to promote integrative behavior during specification are presented.
        Formal models of users' desires and resolution methods are necessary
        for integrative reasoning},
  doi = {10.1109/ICSE.1990.63633},
  keywords = {formal specification;bargaining behavior;integrative behavior;multiagent
        specification design;negotiation;project leader;requirement specification;specification
        acquisition;specification design;Contracts;Eyes;Information science;Protocols;Software
        engineering;Standby generators;Writing}
}

@PHDTHESIS{Rob09,
  author = {Robu},
  title = {Modeling Preferences, Strategic Reasoning and Collaboration in Agent-Mediated
        Electronic Markets},
  school = {Centrum voor Wiskunde en Informatica},
  year = {2009},
  owner = {Mark},
  timestamp = {2013.02.12}
}

@INPROCEEDINGS{Rob05UtilityGraphs,
  author = {Valentin Robu and Johannes A. La Poutr\'{e}},
  title = {Learning the structure of utility graphs used in multi-issue negotiation
        through collaborative filtering},
  booktitle = {Dutch National Research Center for Mathematics and Computer Science},
  year = {2005},
  organization = {Citeseer},
  owner = {Mark},
  timestamp = {2013.02.09}
}

@INPROCEEDINGS{Rob06,
  author = {Valentin Robu and Johannes A. La Poutr\'{e}},
  title = {Retrieving the structure of utility graphs used in multi-item negotiations
        through collaborative filtering of aggregate buyer preferences},
  booktitle = {Proceedings of the 2nd International Workshop on Rational, Robust and Secure Negotiations
        in MAS},
  year = {2006},
  publisher = {Springer},
  owner = {Mark},
  timestamp = {2013.02.11}
}

@INPROCEEDINGS{Rob05,
 author = {Valentin Robu and Koye Somefun and Johannes A. La Poutr\'{e}},
 title = {Modeling Complex Multi-issue Negotiations Using Utility Graphs},
 booktitle = {Proceedings of the Fourth International Joint Conference on Autonomous Agents and Multiagent Systems},
 series = {AAMAS '05},
 year = {2005},
 isbn = {1-59593-093-0},
 location = {The Netherlands},
 pages = {280--287},
 numpages = {8},
 url = {http://doi.acm.org/10.1145/1082473.1082516},
 doi = {10.1145/1082473.1082516},
 acmid = {1082516},
 publisher = {ACM},
 address = {New York, NY, USA},
 keywords = {decision theory, game theory, graphical models, influence diagrams, market-based methods, negotiation, utility graphs},
} 

@ARTICLE{Rog07,
  author = {Alex D. Rogers and Rajdeep K. Dash and Sarvapali D. Ramchurn and Perukrishnen Vytelingum and Nicholas R. Jennings},
  title = {Coordinating team players within a noisy Iterated Prisoner's Dilemma tournament},
  journal = {Theoretical Computer Science },
  year = {2007},
  volume = {377},
  pages = {243 - 259},
  number = {1-3},
  abstract = {In this paper, we present our investigation into the use of a team
        of players within a noisy Iterated Prisoner's Dilemma (IPD) tournament.
        We show that the members of such a team are able to use a pre-arranged
        sequence of moves that they make at the start of each interaction
        in order to recognise one another, and that by coordinating their
        actions they can increase the chances that one of the team members
        wins the round-robin style tournament. We consider, in detail, the
        factors that influence the performance of this team and we show that
        the problem that the team members face, when they attempt to recognise
        one another within the noisy {IPD} tournament, is exactly analogous
        to the problem, studied in information theory, of communicating reliably
        over a noisy channel. Thus we demonstrate that we can use error-correcting
        codes to implement this recognition, and by doing so, further optimise
        the performance of the team.},
  doi = {10.1016/j.tcs.2007.03.015},
  issn = {0304-3975},
  keywords = {Iterated Prisoner's Dilemma},
  url = {http://www.sciencedirect.com/science/article/pii/S0304397507001831}
}

@ARTICLE{Ros06,
  author = {Ros, Raquel and Sierra, Carles},
  title = {A Negotiation Meta Strategy Combining Trade-off and Concession Moves},
  journal = {Autonomous Agents and Multi-Agent Systems},
  year = {2006},
  volume = {12},
  pages = {163-181},
  doi = {10.1007/s10458-006-5837-z},
  issn = {1387-2532},
  issue = {2},
  keywords = {Negotiation},
  language = {English},
  owner = {Mark},
  publisher = {Kluwer Academic Publishers},
  timestamp = {2013.02.11},
  url = {http://dx.doi.org/10.1007/s10458-006-5837-z}
}

@INPROCEEDINGS{Ros11,
  author = {Rosenfeld, A. and Kraus, S.},
  title = {Using aspiration adaptation theory to improve learning},
  booktitle = {The 10th International Conference on Autonomous Agents and Multiagent
        Systems},
        volume = {1},
  year = {2011},
  pages = {423--430},
  organization = {International Foundation for Autonomous Agents and Multiagent Systems},
  owner = {Mark},
  timestamp = {2013.02.03}
}

@PHDTHESIS{Ros86Thesis,
  author = {Rosenschein, Jeffrey S.},
  title = {Rational interaction: cooperation among intelligent agents},
  year = {1986},
  month = {Jan},
  abstract = {The development of intelligent agents presents opportunities to exploit
        intelligent cooperation. Before this can occur, however, a framework
        must be built for reasoning about interactions. This dissertation
        describes such a framework, and explores strategies of interaction
        among intelligent agents. The formalism developed removes some serious
        restrictions that underlie previous research in distributed artificial
        intelligence, particularly the assumption that the interacting agents
        have identical or nonconflicting goals. The formalism allows each
        agent to make various assumptions about both the goals and the rationality
        of other agents. A hierarchy of rationality assumptions is presented,
        along with an analysis of the consequences that result when an agent
        believes a particularly level in the hierarchy describes other agents'
        rationality. In addition, the formalism presented allows the modeling
        of restrictions on communication and the modeling of binding promises
        among agents.},
  publisher = {Stanford University},
  school = {Stanford University},
  address = {Stanford, CA, USA},
  url = {http://www.osti.gov/scitech/servlets/purl/5310977}
}

@BOOK{Ros94,
  title = {Rules of encounter: designing conventions for automated negotiation among computers},
  publisher = {MIT Press},
  year = {1994},
  author = {Rosenschein, Jeffrey S. and Zlotkin, Gilad},
  address = {Cambridge, MA, USA},
  citeulike-article-id = {4544969},
  citeulike-linkout-0 = {http://portal.acm.org/citation.cfm?id=180311},
  isbn = {0-262-18159-2},
  keywords = {negotiation},
  owner = {tim},
  posted-at = {2009-05-19 14:07:53},
  priority = {3},
  timestamp = {2010.04.15},
  url = {http://portal.acm.org/citation.cfm?id=180311}
}

@INPROCEEDINGS{Ros14,
  author = {Di Napoli, Claudia and Di Nocera, Dario and Rossi, Silvia},
  title = {Negotiating Parking Spaces in Smart Cities},
  booktitle = {Proceeding of the 8th International Workshop on Agents in Traffic and Transportation, in conjunction with AAMAS},
  year = {2014},
}

@ARTICLE{Rou11,
  author = {Roussaki, Ioanna G. and Papaioannou, Ioannis V. and Anagnostou, Miltiades E.},
  title = {Using neural network for early detection of unsuccesful negotiation
        threads},
  journal = {International Journal on Artificial Intelligence Tools},
  year = {2011},
  volume = {20},
  pages = {457--487},
  number = {03},
  owner = {Mark},
  publisher = {World Scientific},
  timestamp = {2013.02.01}
}

@Article{Rub11,
  author   = {Jonathan Rubin and Ian Watson},
  title    = {Computer poker: A review},
  journal  = {Artificial Intelligence},
  year     = {2011},
  volume   = {175},
  pages    = {958 - 987},
  doi      = {http://dx.doi.org/10.1016/j.artint.2010.12.005},
  issn     = {0004-3702},
  keywords = {Computer poker},
  url      = {http://www.sciencedirect.com/science/article/pii/S0004370211000191},
}

@BOOK{rubin1975social,
  title = {The social psychology of bargaining and negotiation},
  publisher = {Academic press},
  year = {1975},
  author = {Rubin, Jeffrey Z. and Brown, Bert R.},
  owner = {---},
  timestamp = {2011.05.29}
}

@ARTICLE{Rub82,
  author = {Rubinstein, Ariel},
  title = {Perfect Equilibrium in a Bargaining Model},
  journal = {Econometrica},
  year = {1982},
  volume = {50},
  pages = {97--109},
  number = {1},
  copyright = {Copyright 1982 The Econometric Society},
  issn = {00129682},
  jstor_articletype = {primary article},
  jstor_formatteddate = {Jan., 1982},
  owner = {tim},
  publisher = {The Econometric Society},
  timestamp = {2010.03.29},
  url = {http://www.jstor.org/stable/1912531}
}

@ARTICLE{Rub82short,
  author = {Rubinstein, Ariel},
  title = {Perfect Equilibrium in a Bargaining Model},
  journal = {Econometrica},
  year = {1982},
  volume = {50},
  pages = {97--109},
  number = {1},
  copyright = {Copyright 1982 The Econometric Society},
  issn = {00129682},
  jstor_articletype = {primary article},
  jstor_formatteddate = {Jan., 1982},
  owner = {tim},
  publisher = {The Econometric Society},
  timestamp = {2010.03.29}
}

@article{San14,
abstract = {A negotiation team is a set of agents with common and possibly also conflicting preferences that forms one of the parties of a negotiation. A negotiation team is involved in two decision making processes simultaneously, a negotiation with the opponents, and an intra-team process to decide on the moves to make in the negotiation. This article focuses on negotiation team decision making for circumstances that require unanimity of team decisions. Existing agent-based approaches only guarantee unanimity in teams negotiating in domains exclusively composed of predictable and compatible issues. This article presents a model for negotiation teams that guarantees unanimous team decisions in domains consisting of predictable and compatible, and alsounpredictable issues. Moreover, the article explores the influence of using opponent, and team member models in the proposing strategies that team members use. Experimental results show that the team benefits if team members employ Bayesian learning to model their teammates' preferences.},
author = {Sanchez-Anguix, Victor and Aydogan, Reyhan and Julian, Vicente and Jonker, Catholijn M.},
doi = {10.1016/j.elerap.2014.05.002},
issn = {15674223},
journal = {Electronic Commerce Research and Applications},
keywords = {Agreement technologies,Automated negotiation,Multi-agent systems},
month = {May},
title = {{Unanimously Acceptable Agreements for Negotiation Teams in Unpredictable Domains}},
url = {http://www.sciencedirect.com/science/article/pii/S1567422314000283},
year = {2014}
}

@ARTICLE{San13evo,
  author = {V\'{i}ctor S{\'a}nchez-Anguix and Soledad Valero and Vicente Juli\'an and Vicente Botti and Ana Garc{\'\i}a-Fornes},
  title = {Evolutionary-aided negotiation model for bilateral bargaining in     Ambient Intelligence domains with complex utility functions},
  journal = {Information Sciences },
  year = {2013},
  volume = {222},
  pages = {25 - 46},
  abstract = {Ambient Intelligence aims to offer personalized services and easier
        ways of interaction between people and systems. Since several users
        and systems may coexist in these environments, it is quite possible
        that entities with opposing preferences need to cooperate to reach
        their respective goals. Automated negotiation is pointed as one of
        the mechanisms that may provide a solution to this kind of problems.
        In this article, a multi-issue bilateral bargaining model for Ambient
        Intelligence domains is presented where it is assumed that agents
        have computational bounded resources and do not know their opponents'
        preferences. The main goal of this work is to provide negotiation
        models that obtain efficient agreements while maintaining the computational
        cost low. A niching genetic algorithm is used before the negotiation
        process to sample one's own utility function (self-sampling). During
        the negotiation process, genetic operators are applied over the opponent's
        and one's own offers in order to sample new offers that are interesting
        for both parties. Results show that the proposed model is capable
        of outperforming similarity heuristics which only sample before the
        negotiation process and of obtaining similar results to similarity
        heuristics which have access to all of the possible offers. },
  doi = {http://dx.doi.org/10.1016/j.ins.2010.11.018},
  issn = {0020-0255},
  keywords = {Automated negotiation},
  url = {http://www.sciencedirect.com/science/article/pii/S0020025510005633}
}

@PHDTHESIS{San13complex,
  author = {S{\'a}nchez-Anguix, V{\'\i}ctor},
  title = {Complex Negotiations in Multi-Agent Systems},
  school = {Departament de Sistemes Inform{\`a}tics i Computaci{\'o}, Universitat Polit{\`e}cnica de Val{\`e}ncia},
  year = {2013}
}

@CONFERENCE{San12,
  author = {S{\'a}nchez-Anguix, V{\'\i}ctor and Reyhan Aydo{\u{g}}an and Vicente Julian and Catholijn M. Jonker},
  title = {Analysis of Intra-Team Strategies for Teams Negotiating Against Competitor, Matchers, and Conceders},
  booktitle = {The Fifth International Workshop on Agent-based Complex Automated Negotiations (ACAN 2012)},
  year = {2012},
  address = {Valencia, Spain}
}

@ARTICLE{San13,
  author = {S{\'a}nchez-Anguix, V{\'\i}ctor and Valero, Soledad and Juli{\'a}n, Vicente and Botti, Vicente and Garc{\'\i}a-Fornes, Ana},
  title = {Evolutionary-aided negotiation model for bilateral bargaining in     Ambient Intelligence domains with complex utility functions},
  journal = {Information Sciences},
  year = {2013},
  volume = {222},
  pages = {25 - 46},
  number = {0},
  doi = {10.1016/j.ins.2010.11.018},
  issn = {0020-0255},
  keywords = {Automated negotiation},
  owner = {Mark},
  timestamp = {2013.06.02},
  url = {http://www.sciencedirect.com/science/article/pii/S0020025510005633}
}

@TECHREPORT{San04,
  author = {S\'{a}nchez-Pag\'{e}s, Santiago},
  title = {The use of conflict as a bargaining tool against unsophisticated     opponents},
  institution = {Edinburgh School of Economics, University of Edinburgh},
  year = {2004},
  month={Mar},
  type = {{ESE} Discussion Papers},
  number={99},
  abstract = {In this paper we explore the role of conflict as an informational
        device by means of a simple bargaining model with one-sided incomplete
        information: Limited conflicts reveal information about the outcome
        of the all-out conflict (that ends the game) because the outcomes
        of both types of confrontations are driven by the relative strength
        of the parties. We limit the analysis to the case where the uninformed
        party can learn the information transmitted in the battlefield but
        not the one conveyed by offers. The game becomes then an optimal
        stopping problem where the informed party has to decide at each period
        whether to stop, by reaching an agreement or by invoking total conflict,
        or to keep fighting. We show that conflict is a double-edge sword:
        It may paradoxically open the door to agreement when the uniformed
        party is too optimistic. But confrontation also occurs when agreement
        is possible but the informed agent has incentives to improve her
        bargaining position by fighting.},
  keywords = {Relative strength; absolute conflict; battles; unsophisticated opponent;
        optimal stopping.},
  url = {http://EconPapers.repec.org/RePEc:edn:esedps:99}
}

@ARTICLE{Sah06,
  author = {Saha, S.},
  title = {Improving Agreements in Multi-issue Negotiation},
  journal = {Journal of Electronic Commerce Research},
  year = {2006},
  volume = {7},
  pages = {41--49},
  number = {1},
  owner = {Mark},
  timestamp = {2013.02.11}
}

@INPROCEEDINGS{Sah05,
  author = {Saha, Sabyasachi and Biswas, Anish and Sen, Sandip},
  title = {Modeling opponent decision in repeated one-shot negotiations},
  booktitle = {Proceedings of the fourth international joint conference on autonomous agents and multiagent systems},
  year = {2005},
  series = {AAMAS '05},
  pages = {397--403},
  address = {New York, NY, USA},
  publisher = {ACM},
  acmid = {1082534},
  doi = {http://doi.acm.org/10.1145/1082473.1082534},
  isbn = {1-59593-093-0},
  keywords = {chebychev polynomial, learning, negotiation},
  location = {The Netherlands},
  numpages = {7},
  owner = {tim},
  timestamp = {2011.03.03},
  url = {http://doi.acm.org/10.1145/1082473.1082534}
}

@incollection{Sah05Bayesnet,
year={2005},
isbn={978-3-540-24526-1},
booktitle={Argumentation in Multi-Agent Systems},
volume={3366},
series={Lecture Notes in Computer Science},
editor={Rahwan, Iyad and Mora\"{i}tis, Pavlos and Reed, Chris},
doi={10.1007/978-3-540-32261-0_14},
title={A Bayes Net Approach to Argumentation Based Negotiation},
url={http://dx.doi.org/10.1007/978-3-540-32261-0_14},
publisher={Springer Berlin Heidelberg},
author={Saha, Sabyasachi and Sen, Sandip},
pages={208-222},
language={English}
}

@ARTICLE{San07,
  author = {Sandholm, T.},
  title = {Expressive commerce and its application to sourcing: How we conducted
        \$35 billion of generalized combinatorial auctions},
  journal = {AI Magazine},
  year = {2007},
  volume = {28},
  pages = {45-58},
  number = {3}
}

@inproceedings{San95,
  title         = {Issues in automated negotiation and electronic commerce: Extending the contract net framework},
  author        = {Sandholm, Tuomas and Lesser, Victor R},
  booktitle = {Proceedings of the First International Conference on Multi-Agent Systems {(ICMAS)}},
  pages         = "328--335",
  address       = "San Francisco, CA",
  year          = {1995}
}

@INPROCEEDINGS{San96,
  author = {Tuomas Sandholm and Victor R. Lesser},
  title = {Advantages of a Leveled Commitment Contracting Protocol},
  booktitle = {Proceedings of the Thirteenth National Conference on Artificial Intelligence
        and Eighth Innovative Applications of Artificial Intelligence Conference,
        AAAI 96, IAAI 96, Portland, Oregon, August 4-8, 1996},
        volume = {1},
  year = {1996},
  editor = {William J. Clancey and Daniel S. Weld},
  pages = {126-133},
  publisher = {AAAI Press / The MIT Press},
  bibsource = {DBLP, http://dblp.uni-trier.de},
  ee = {http://www.aaai.org/Conferences/AAAI/aaai96.php},
  isbn = {ISBN 0-262-51091-X}
}

@INPROCEEDINGS{San99,
  author = {Sandholm, Tuomas and Vulkan, Nir},
  title = {Bargaining with deadlines},
  booktitle = {Proceedings of the sixteenth national conference on Artificial intelligence and the eleventh Innovative applications of artificial intelligence conference},
  year = {1999},
  series = {AAAI '99/IAAI '99},
  pages = {44--51},
  address = {Menlo Park, CA, USA},
  publisher = {American Association for Artificial Intelligence},
  acmid = {315224},
  isbn = {0-262-51106-1},
  location = {Orlando, Florida, USA},
  numpages = {8},
  url = {http://dl.acm.org/citation.cfm?id=315149.315224}
}
@article{San99dist,
  title={Distributed rational decision making},
  author={Sandholm, Tuomas W},
  journal={Multiagent systems: a modern approach to distributed artificial intelligence},
  pages={201--258},
  year={1999}
}

@book{San10,
  title={Population games and evolutionary dynamics},
  author={Sandholm, William H.},
  year={2010},
  publisher={MIT press}
}

@INPROCEEDINGS{Scha07,
  author = {Frederik Christiaan Schadd and Sander Bakkes and Pieter H.M. Spronck},
  title = {Opponent modeling in real-time strategy games},
  booktitle = {8th International Conference on Intelligent Games and Simulation (GAME-ON 2007)},
  year = {2007},
  pages = {61--68},
  owner = {Mark},
  timestamp = {2012.07.18}
}

@ARTICLE{Sch06,
  author = {Schatzmann, Jost and Weilhammer, Karl and Stuttle, Matt and Young,
        Steve},
  title = {A survey of statistical user simulation techniques for reinforcement-learning
        of dialogue management strategies},
  journal = {The Knowledge Engineering Review},
  year = {2006},
  volume = {21},
  pages = {97--126},
  number = {2},
  month = {Jun},
  acmid = {1166054},
  address = {New York, NY, USA},
  doi = {10.1017/S0269888906000944},
  issn = {0269-8889},
  issue_date = {June 2006},
  numpages = {30},
  publisher = {Cambridge University Press},
  url = {http://dx.doi.org/10.1017/S0269888906000944}
}

@ARTICLE{Sche56,
  author = {Schelling, Thomas C.},
  title = {An Essay on Bargaining},
  journal = {The American Economic Review},
  year = {1956},
  volume = {46},
  pages = {281--306},
  number = {3},
  copyright = {Copyright 1956 American Economic Association},
  issn = {00028282},
  jstor_articletype = {primary article},
  jstor_formatteddate = {Jun., 1956},
  owner = {tim},
  publisher = {American Economic Association},
  timestamp = {2010.07.20},
  url = {http://www.jstor.org/stable/1805498}
}

@ARTICLE{Schn02,
  author = {Schneider, A.K.},
  title = {Shattering negotiation myths: Empirical evidence on the effectiveness
        of negotiation style},
  journal = {Harv. Negot. L. Rev.},
  year = {2002},
  volume = {7},
  pages = {143},
  owner = {Mark},
  publisher = {HeinOnline},
  timestamp = {2012.01.08}
}

@ARTICLE{Sco66,
  author = {John T. Scott Jr.},
  title = {Factor Analysis and Regression},
  journal = {Econometrica},
  year = {1966},
  volume = {34},
  pages = {pp. 552-562},
  number = {3},
  abstract = {This paper derives a stochastic linear equation from factor analysis
        called factor analysis regression which is suggested as an alternative
        to classical least squares regression whenever least squares estimation
        is questionable or breaks down because of errors in the variables
        or multicollinearity. Statistical tests for the factor analysis regression
        are also suggested and an empirical example comparing factor-analysis
        regression with least squares is shown.},
  copyright = {Copyright 1966 The Econometric Society},
  issn = {00129682},
  jstor_articletype = {research-article},
  jstor_formatteddate = {Jul., 1966},
  language = {English},
  publisher = {The Econometric Society},
  url = {http://www.jstor.org/stable/1909769}
}

@INPROCEEDINGS{ANAC2010SerExt,
  author = {Liviu Dan \c{S}erban and Gheorghe Cosmin Silaghi and Cristian Marius Litan},
  title = {Agent{FSEGA} - Time Constrained Reasoning Model for Bilateral Multi-Issue Negotiations},
  booktitle = {New Trends in Agent-based Complex Automated Negotiations, Series of
        Studies in Computational Intelligence},
  year = {2012},
  editor = {Takayuki Ito and Minjie Zhang and Valentin Robu and Shaheen Fatima
        and Tokuro Matsuo},
  pages = {159-165},
  address = {Berlin, Heidelberg},
  publisher = {Springer-Verlag},
  isbn = {978-3-642-24695-1},
  owner = {tim}
}

@ARTICLE{ANAC2010Ser,
  author = {Liviu Dan \c{S}erban and Gheorghe Cosmin Silaghi and Cristian Marius
        Litan},
  title = {Agent{FSEGA} - Time Constrained Reasoning Model for Bilateral Multi-IssueNegotiations},
  journal = {This volume},
  year = {2012},
  pages = {159-165}
}

@INCOLLECTION{Ser13,
  author = {\c{S}erban, Liviu Dan and Stefanache, Cristina Maria and Silaghi, Gheorghe Cosmin and Litan, Cristian Marius},
  title = {A Qualitative Ascending Protocol for Multi-issue One-to-Many Negotiations},
  booktitle = {Complex Automated Negotiations: Theories, Models, and Software Competitions},
  publisher = {Springer Berlin Heidelberg},
  year = {2013},
  editor = {Ito, Takayuki and Zhang, Minjie and Robu, Valentin and Matsuo, Tokuro},
  volume = {435},
  series = {Studies in Computational Intelligence},
  pages = {143-159},
  doi = {10.1007/978-3-642-30737-9\_9},
  isbn = {978-3-642-30736-2},
  url = {http://dx.doi.org/10.1007/978-3-642-30737-9\_9}
}

@PHDTHESIS{Sha13,
  author = {Sharma, Ashwini},
  title = {A study on adoption of e-Negotiation through software agents},
  year = {2013},
  url = {http://hdl.handle.net/10603/10155}
}

@ARTICLE{sha,
  author = {Sharma, Ashwini and Pandel, Upender},
  title = {A study of Traditional Negotiation and Electronic Negotiation},
  journal = {International Journal of Engineering Research and Applications (IJERA)},
  volume = {1},
  issn = {2248-9622 },
  issue = {2},
  page = {153-156},
  url = {http://www.ijera.com/papers/vol\%201\%20issue\%202/012153156Q.pdf}
}

@ARTICLE{She98,
  author = {Onn Shehory and Sarit Kraus},
  title = {Methods for task allocation via agent coalition formation},
  journal = {Artificial Intelligence},
  year = {1998},
  volume = {101},
  pages = {165 - 200},
  number = {1-2},
  abstract = {Task execution in multi-agent environments may require cooperation
        among agents. Given a set of agents and a set of tasks which they
        have to satisfy, we consider situations where each task should be
        attached to a group of agents that will perform the task. Task allocation
        to groups of agents is necessary when tasks cannot be performed by
        a single agent. However it may also be beneficial when groups perform
        more efficiently with respect to the single agents' performance.
        In this paper we present several solutions to the problem of task
        allocation among autonomous agents, and suggest that the agents form
        coalitions in order to perform tasks or improve the efficiency of
        their performance. We present efficient distributed algorithms with
        low ratio bounds and with low computational complexities. These properties
        are proven theoretically and supported by simulations and an implementation
        in an agent system. Our methods are based on both the algorithmic
        aspects of combinatorics and approximation algorithms for NP-hard
        problems. We first present an approach to agent coalition formation
        where each agent must be a member of only one coalition. Next, we
        present the domain of overlapping coalitions. We proceed with a discussion
        of the domain where tasks may have a precedence order. Finally, we
        discuss the case of implementation in an open, dynamic agent system.
        For each case we provide an algorithm that will lead agents to the
        formation of coalitions, where each coalition is assigned a task.
        Our algorithms are any-time algorithms, they are simple, efficient
        and easy to implement. },
  doi = {http://dx.doi.org/10.1016/S0004-3702(98)00045-9},
  issn = {0004-3702},
  keywords = {Task allocation },
  url = {http://www.sciencedirect.com/science/article/pii/S0004370298000459}
}

@ARTICLE{Shi13,
  author = {Shi, Bing and Gerding, Enrico H. and Vytelingum, Perukrishnen and Jennings, Nicholas R.},
  title = {An equilibrium analysis of market selection strategies and fee strategies in competing double auction marketplaces},
  journal = {Autonomous Agents and Multi-Agent Systems},
  year = {2013},
  volume = {26},
  pages = {245-287},
  number = {2},
  doi = {10.1007/s10458-011-9190-5},
  issn = {1387-2532},
  keywords = {Competing double auction marketplaces; Market selection strategy;
        Fee strategy; Evolutionary game theory; Co-evolutionary approach},
  language = {English},
  publisher = {Springer US},
  url = {http://dx.doi.org/10.1007/s10458-011-9190-5}
}

@INPROCEEDINGS{Sie12negoandsearch,
  author = {Sierra, Carles},
  title = {Negotiation and Search},
  booktitle = {AT},
  year = {2012},
  pages = {1}
}

@INPROCEEDINGS{Sie97,
  author = {Carles Sierra and Peyman Faratin and Nicholas R. Jennings},
  title = {A service-oriented negotiation model between autonomous agents},
  booktitle = {Proceedings of the 8th European Workshop on Modelling Autonomous
        Agents in Multi-Agent World, MAAMAW-97},
  year = {1997},
  editor = {Magnus Boman and Walter van de Velde},
  volume = {1237},
  isbn={978-3-540-63077-7},
  series = {Lecture Notes in Artificial Intelligence},
  pages = {17-35},
  publisher = {Springer-Verlag}
}

@INPROCEEDINGS{Sil10,
  author = {Gheorghe Cosmin Silaghi and Liviu Dan \c{S}erban and Cristian Marius Litan},
  title = {A framework for building intelligent {SLA} negotiation strategies
        under time constraints},
  booktitle = {Proceedings of Economics of Grids, Clouds, Systems, and Services:
        7th International Workshop},
  year = {2010},
  editor={Altmann, J\"{o}rn and Rana, Omer F.},
  volume = {6296},
  pages = {48},
  organization = {Springer-Verlag New York Inc},
  owner = {---},
  timestamp = {2011.06.19}
}

@ARTICLE{Sil12,
  author = {Silaghi, Gheorghe Cosmin and \c{S}erban, Liviu Dan and Litan, Cristian
        Marius},
  title = {A time-constrained {SLA} negotiation strategy in competitive computational
        grids},
  journal = {Future Generation Computer Systems},
  year = {2012},
  volume = {28},
  pages = {1303--1315},
  number = {8},
  publisher = {Elsevier}
}

@ARTICLE{Sim09,
author={Kwang Mong Sim and Yuanyuan Guo and Benyun Shi}, 
journal={IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics}, 
title={{BLGAN}: Bayesian Learning and Genetic Algorithm for Supporting Negotiation With Incomplete Information}, 
year={2009}, 
month={Feb}, 
volume={39}, 
number={1}, 
pages={198-211}, 
keywords={Bayes methods;genetic algorithms;learning (artificial intelligence);BLGAN;Bayesian learning;automated negotiation;combined negotiation outcomes;deadline-estimation process;genetic algorithm;mathematical proofs;optimal strategy;reserve price;search space;Automated negotiation;Bayesian learning (BL);genetic algorithms (GAs);intelligent agents;negotiation agents;Algorithms;Artificial Intelligence;Automation;Bayes Theorem;Computer Simulation;Humans;Models, Theoretical;Negotiating}, 
doi={10.1109/TSMCB.2008.2004501}, 
ISSN={1083-4419},}

@InProceedings{Sim09Cloud,
  author    = {Kwang-Mong Sim},
  title     = {Agent-based Cloud commerce},
  booktitle = {IEEE International Conference on Industrial Engineering and Engineering Management},
  year      = {2009},
  pages     = {717-721},
  doi       = {10.1109/IEEM.2009.5373228},
  keywords  = {Internet;electronic commerce;multi-agent systems;ubiquitous computing;4-stage resource discovery process;SLA negotiation;agent-based cloud commerce;business model;cloud computing;cloud resources;consumer agents;e-commerce;electronic commerce;grid computing;service level agreement;Business communication;Cloud computing;Costs;Electronic mail;Matched filters;Pervasive computing;Physics computing;Resource management;Resource virtualization;Testing;Cloud/Grid computing;e-Commerce;multiagent systems;negotiation;resource management},
}

@INPROCEEDINGS{Sim07,
  author = {Sim, Kwang Mong and Guo, Yuanyuan and Shi, Benyun},
  title = {Adaptive bargaining agents that negotiate optimally and rapidly},
  booktitle = {IEEE Congress on Evolutionary Computation},
  year = {2007},
  month={Sep}, 
  pages = {1007--1014},
  organization = {IEEE},
  owner = {Mark},
  doi={10.1109/CEC.2007.4424580},
  timestamp = {2013.06.01}
}

@ARTICLE{Ski12,
  author = {Skinner, Brian},
  title = {The Problem of Shot Selection in Basketball},
  journal = {PLoS ONE},
  year = {2012},
  volume = {7},
  pages = {e30776},
  number = {1},
  month = {Jan},
  abstract = {In basketball, every time the offense produces a shot opportunity
        the player with the ball must decide whether the shot is worth taking.
        In this article, I explore the question of when a team should shoot
        and when they should pass up the shot by considering a simple theoretical
        model of the shot selection process, in which the quality of shot
        opportunities generated by the offense is assumed to fall randomly
        within a uniform distribution. Within this model I derive an answer
        to the question how likely must the shot be to go in before the player
        should take it? and I show that this lower cutoff for shot quality
        <inline-formula><inline-graphic xmlns:xlink="http://www.w3.org/1999/xlink"
        xlink:href="info:doi/10.1371/journal.pone.0030776.e001" mimetype="image"
        xlink:type="simple"/></inline-formula> depends crucially on the number
        <inline-formula><inline-graphic xmlns:xlink="http://www.w3.org/1999/xlink"
        xlink:href="info:doi/10.1371/journal.pone.0030776.e002" mimetype="image"
        xlink:type="simple"/></inline-formula> of shot opportunities remaining
        (say, before the shot clock expires), with larger <inline-formula><inline-graphic
        xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="info:doi/10.1371/journal.pone.0030776.e003"
        mimetype="image" xlink:type="simple"/></inline-formula> demanding
        that only higher-quality shots should be taken. The function <inline-formula><inline-graphic
        xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="info:doi/10.1371/journal.pone.0030776.e004"
        mimetype="image" xlink:type="simple"/></inline-formula> is also derived
        in the presence of a finite turnover rate and used to predict the
        shooting rate of an optimal-shooting team as a function of time.
        The theoretical prediction for the optimal shooting rate is compared
        to data from the National Basketball Association (NBA). The comparison
        highlights some limitations of the theoretical model, while also
        suggesting that NBA teams may be overly reluctant to shoot the ball
        early in the shot clock.},
  doi = {10.1371/journal.pone.0030776},
  publisher = {Public Library of Science},
  url = {http://dx.doi.org/10.1371%2Fjournal.pone.0030776}
}

@TECHREPORT{Sle99,
title = {Reputations and Fairness in Bargaining - Experimental Evidence from a Repeated Ultimatum Game With Fixed Opponents},
author = {Slembeck, Tilman},
year = {1999},
institution = {EconWPA},
type = {Experimental},
abstract = {The results of Ultimatum Game experiments are often quoted as evidence for the role of fairness in bargaining or in economic behaviour more generally. This paper argues that the observed fairness levels are contingent on the traditional experimental design where players are newly matched each round, and reputations are therefore excluded. Evidence from a new experiment shows that average behaviour is more competitive and conflict rates are higher when subjects play against the same opponent repeatedly. This finding is not expected by the traditional fairness hypothesis. A detailed analysis of the dynamics of pairs of players shows that different types of players coexist in the subject pool. Whereas previous experiments found evidence for the existence of fair players, the present study reports also a significant number of tough players. Hence, there is evidence that allowing for reputations in repeated ultimatum bargaining induces different patterns of behaviour that have not been observed before in this game.},
keywords = {game theory; experiments; learning; fairness; reputations; ultimatum game},
url = {http://EconPapers.repec.org/RePEc:wpa:wuwpex:9905002}
}

@BOOK{Smi82,
  title = {Evolution and the Theory of Games},
  publisher = {Cambridge University Press},
  year = {1982},
  author = {Smith, J.},
  address = {Cambridge, United Kingdom}
}

@ARTICLE{Smi80,
  author = {Smith, Reid G.},
  title = {The Contract Net Protocol: High-Level Communication and Control in a Distributed Problem Solver},
  journal = {IEEE Transactions on Computers},
  year = {1980},
  month = {Dec},
  volume = {29},
  issn = {0018-9340},
  pages = {1104-1113},
  number = {12},
  publisher = {IEEE Computer Society},
 address = {Washington, DC, USA},
  abstract = {The contract net protocol has been developed to specify problem-solving
        communication and control for nodes in a distributed problem solver.
        Task distribution is affected by a negotiation process, a discussion
        carried on between nodes with tasks to be executed and nodes that
        may be able to execute those tasks.},
  doi = {10.1109/TC.1980.1675516},
  issn = {0018-9340},
  keywords = {Artificial Intelligence (AI);connection;cooperation;distributed problem
        solving;focus;high-level protocols;negotiation;resource allocation;task-sharing;Communication
        system control;Communication system traffic control;Contracts;Distributed
        control;Memory;Problem-solving;Production;Protocols;Resource management;Telecommunication
        network reliability;Artificial Intelligence (AI);connection;cooperation;distributed
        problem solving;focus;high-level protocols;negotiation;resource allocation;task-sharing}
}

@ARTICLE{Sob83,
  author = {Sobel, Joel and Takahashi, Ichiro},
  title = {A Multistage Model of Bargaining},
  journal = {The Review of Economic Studies},
  year = {1983},
  volume = {50},
  pages = {411--426},
  number = {3},
  abstract = {This paper presents a simple, multistage model of bargaining wherein
        a seller makes an offer that can be either accepted or refused. If
        rejected, the process continues. How the seller's ability to make
        commitments affects bargaining outcomes is analysed by comparing
        the commitment equilibria to those arising when commitment is impossible.
        The effects of increasing uncertainty about preferences and varying
        the length of the bargaining horizon are analysed. The ways in which
        the bargaining environment can be changed to improve outcomes are
        discussed.},
  copyright = {Copyright 1983 The Review of Economic Studies Ltd.},
  issn = {00346527},
  jstor_articletype = {primary article},
  jstor_formatteddate = {Jul., 1983},
  owner = {tim},
  publisher = {The Review of Economic Studies Ltd.},
  timestamp = {2010.04.01},
  url = {http://www.jstor.org/stable/2297673}
}

@INPROCEEDINGS{Sof12,
  author = {Israel Sofer and David Sarne and Avinatan Hassidim},
  title = {Negotiation in Exploration-based Environment },
  booktitle = {Proceedings of the Twenty-Sixth AAAI Conference on Artificial Intelligence},
  year = {2012}
}

@incollection{Som04InformationGoods,
author={Koye Somefun and Enrico H. Gerding and Sander Bohte and Johannes A. La Poutr\'{e}},
title={Automated Negotiation and Bundling of Information Goods},
year={2004},
isbn={978-3-540-22674-1},
booktitle={Agent-Mediated Electronic Commerce V. Designing Mechanisms and Systems},
volume={3048},
series={Lecture Notes in Computer Science},
editor={Faratin, Peyman and Parkes, David C. and Rodr\'{i}guez-Aguilar, Juan A. and Walsh, William E.},
doi={10.1007/978-3-540-25947-3_1},
url={http://dx.doi.org/10.1007/978-3-540-25947-3_1},
publisher={Springer Berlin Heidelberg},
pages={1-17},
language={English}
}


@ARTICLE{Som04Aggregate,
  author = {Koye Somefun and Tomas B. Klos and Johannes A. La Poutr\'{e}},
  title = {Negotiating over bundles and prices using aggregate knowledge},
  journal = {E-Commerce and Web Technologies},
  year = {2004},
  volume = {3182},
  pages = {259--266},
  owner = {Mark},
  publisher = {Springer},
  timestamp = {2013.02.01}
}

@incollection{Som07,
author = {Koye Somefun and Johannes A. La Poutr\'{e}},
title={A Fast Method for Learning Non-linear Preferences Online Using Anonymous Negotiation Data},
year={2007},
isbn={978-3-540-72501-5},
booktitle={Agent-Mediated Electronic Commerce. Automated Negotiation and Strategy Design for Electronic Markets},
volume={4452},
series={Lecture Notes in Computer Science},
editor={Fasli, Maria and Shehory, Onn},
doi={10.1007/978-3-540-72502-2_9},
url={http://dx.doi.org/10.1007/978-3-540-72502-2_9},
publisher={Springer Berlin Heidelberg},
pages={118-131},
language={English}
}


@INPROCEEDINGS{Som06,
  author = {Koye Somefun and Johannes A. La Poutr\'{e}},
  title = {A scalable method for online learning of non-linear preferences based on anonymous negotiation data},
  booktitle = {Proceedings of the fifth international joint conference on Autonomous agents and multiagent systems},
  year = {2006},
  pages = {417--419},
  organization = {ACM},
  owner = {Mark},
  timestamp = {2013.02.06}
}

@MISC{Som04,
  author = {Koye Somefun and Tomas B. Klos and Johannes A. La Poutr\'{e}},
  title = {Online Learning of Aggregate Knowledge about Nonlinear Preferences Applied to Negotiating Prices and Bundles},
  year = {2004},
  pages = {361-370},
  publisher = {ACM}
}

@BOOK{Sta72,
  title = {Bargaining theory},
  publisher = {Economic Research Institute, Stockholm},
  year = {1972},
  author = {Stahl, Ingolf},
  pages = {313},
  catalogue-url = { http://nla.gov.au/nla.cat-vn1772672 },
  language = {English},
  subjects = {Negotiation - Mathematical models.; Game theory.; Oligopolies - Mathematical
        models.},
  type = {Book}
}

@ARTICLE{Sto05,
  author = {Peter Stone and Amy Greenwald},
  title = {The First International Trading Agent Competition: Autonomous Bidding
        Agents},
  journal = {Electronic Commerce Research},
  year = {2005},
  volume = {5},
  pages = {229--265},
  number = {2},
  month = {Apr},
  abstract = { This article summarizes the bidding algorithms developed for the
        on-line Trading Agent Competition held in July, 2000 in Boston. At
        its heart, the article describes 12 of the 22 agent strategies in
        terms of (i) bidding strategy, (ii) allocation strategy, (iii) special
        approaches, and (iv) team motivations. The common and distinctive
        features of these agent strategies are highlighted. In addition,
        experimental results are presented that give some insights as to
        why the top-scoring agents' strategies were most effective. },
  owner = {tim},
  timestamp = {2010.06.03},
}

@ARTICLE{Sut03,
  author = {Matthias Sutter and Martin Kocher and Sabine Strau{\ss}},
  title = {Bargaining under time pressure in an experimental ultimatum game},
  journal = {Economics Letters},
  year = {2003},
  volume = {81},
  pages = {341 - 347},
  number = {3},
  abstract = {We examine the influence of time pressure on bargaining behavior in
        an ultimatum game. Controlling for offers, rejection rates of responders
        are significantly higher under a tight than under a very weak time
        constraint. However, this effect vanishes with repetition.},
  doi = {DOI: 10.1016/S0165-1765(03)00215-5},
  issn = {0165-1765},
  keywords = {Time pressure},
  owner = {tim},
  timestamp = {2011.03.11},
  url = {http://www.sciencedirect.com/science/article/B6V84-49S7771-3/2/c9dd5db5423a6ba23ada39588ab1e1e4}
}

@ARTICLE{Sut86,
  author = {Sutton, John},
  title = {Non-Cooperative Bargaining Theory: An Introduction},
  journal = {The Review of Economic Studies},
  year = {1986},
  volume = {53},
  pages = {709--724},
  number = {5},
  abstract = {The paper provides an informal introduction to some of the main themes
        of the recent literature on "non-cooperative" or "sequential" bargaining
        models. It focuses in particular on the relationship between the
        new approach and the traditional axiomatic approach exemplified by
        "Nash bargaining theory". It illustrates the new insights offered
        by the non-cooperative approach, by reference to a detailed analysis
        of the manner in which the presence of an outside option available
        to one of the parties will affect the negotiated outcome. Finally,
        the difficulties which arise in extending this analysis to two-person
        bargaining with incomplete information, and to n-person bargaining,
        are discussed. This is a revised version of the fourth Review of
        Economic Studies Lecture presented in April 1985 at the joint meeting
        of the Association of University Teachers of Economics and the Royal
        Economic Society held in Oxford. The choice of lecturer is made by
        a panel whose members are currently Professors Hahn, Mirrlees and
        Nobay, and the paper is refereed in the usual way.},
  copyright = {Copyright 1986 The Review of Economic Studies Ltd.},
  issn = {00346527},
  jstor_articletype = {primary article},
  jstor_formatteddate = {Oct., 1986},
  owner = {tim},
  publisher = {The Review of Economic Studies Ltd.},
  timestamp = {2010.03.29},
  url = {http://www.jstor.org/stable/2297715}
}

@ARTICLE{Syc93,
  author = {Katia P. Sycara},
  title = {Machine learning for intelligent support of conflict resolution},
  journal = {Decision Support Systems},
  year = {1993},
  volume = {10},
  pages = {121 - 136},
  number = {2},
  abstract = {Because negotiation and conflict resolution are complex and unstructured
        tasks, they need sophisticated decision support. One of the crucial
        characteristics of such support is systems that are capable of improving
        their performance, both in terms of efficiency and solution quality,
        by employing machine learning techniques. A framework for intelligent
        computer-supported conflict resolution through negotiation/ mediation
        is presented. The model integrates Artificial Intelligence methods
        (case-based reasoning) and decision theoretic techniques (multi-attribute
        utilities) to provide enhanced conflict resolution and negotiation
        support in group problem solving. This model has been implemented
        in the PERSUADER, a computer program which operates in the domain
        of resolution of labor management disputes. The PERSUADER uses case-based
        reasoning (CBR) to learn from its experience. In contrast to quantitative
        models or expert systems that solve each problem from scratch and
        discard the solution at the end of problem solving, CBR retains the
        process and results of its computational decisions so that they can
        be re-used to solve future related problems. CBR is a powerful learning
        method since it enables a system not only to exploit previous succesful
        decisions, thus short-cutting possibly long reasoning chains, but
        also to profit from previous failures by using them to recognize
        similar failures in advance so they can be avoided in the future.
        As the state of the art in DSS development advances and as DSSs support
        increasingly more complicated tasks, such machine learning techniques
        will become an indispensable part of decision support systems.},
  doi = {10.1016/0167-9236(93)90034-Z},
  issn = {0167-9236},
  keywords = {Learning},
  owner = {tim},
  timestamp = {2012.02.14},
  url = {http://www.sciencedirect.com/science/article/pii/016792369390034Z}
}

@ARTICLE{Syc90,
  author = {Sycara, Katia P.},
  title = {Persuasive argumentation in negotiation},
  journal = {Theory and Decision},
  year = {1990},
  volume = {28},
  pages = {203-242},
  abstract = {This paper presents Persuasive Argumentation as a means of guiding
        the negotiation process to a settlement. Decision theoretic approaches
        construct prescriptive models of the negotiation process that make
        various assumptions about the behavior of the negotiation participants
        but do not model changes in behavior. On the other hand, models for
        decision support leave the actual decisions to human negotiators,
        again not modeling or automating the negotiating process. In contrast
        to both approaches, our work deals with automating the negotiation
        process. This paper focuses on modeling the process by which the
        beliefs and behavior of negotiators are changed via persuasive argumentation.
        We claim that persuasive argumentation lies at the heart of negotiation
        and embodies the dynamics of negotiation. We present a model of persuasive
        argumentation that integrates Artificial Intelligence and decision
        theoretic methods. The model has been implemented as part of the
        PERSUADER, a multi-agent computer program that operates in the domain
        of labor negotiations.},
  issn = {0040-5833},
  issue = {3},
  keyword = {Business and Economics},
  publisher = {Springer Netherlands},
  url = {http://dx.doi.org/10.1007/BF00162699}
}

@INPROCEEDINGS{Syc88,
  author = {Sycara, Katia P.},
  title = {Resolving Goal Conflicts via Negotiation},
  booktitle = {Proceedings of the 7th National Conference on Artificial Intelligence.
               St. Paul, MN, August 21-26, 1988.},
  year = {1988},
  pages = {245--250}
}

@inproceedings{Syc85,
  author = {Sycara, Katia P.},
 title = {Arguments of Persuasion in Labour Mediation},
 booktitle = {Proceedings of the 9th International Joint Conference on Artificial Intelligence},
 volume = {1},
 year = {1985},
 isbn = {0-934613-02-8},
 location = {Los Angeles, California},
 pages = {294--296},
 numpages = {3},
 url = {http://dl.acm.org/citation.cfm?id=1625135.1625190},
 acmid = {1625190},
 publisher = {Morgan Kaufmann Publishers Inc.},
 address = {San Francisco, CA, USA},
} 


@INPROCEEDINGS{Syk10,
  author = {Adam M. Sykulski and Archie C. Chapman and Enrique Munoz de Cote and Nicholas R. Jennings},
  title = {EA Squared: The Winning Strategy for the Inaugural Lemonade Stand Game Tournament},
  booktitle = {Proc. of the Nineteenth European Conference on Artificial Intelligence,
        Lisbon, Portugal},
  year = {2010},
  pages = {209-214}
}

@ARTICLE{Tei04,
  author = {Teich, J.E. and Wallenius, H. and Wallenius, J. and Koppius, O.R.},
  title = {Emerging multiple issue e-auctions},
  journal = {European Journal of Operational Research},
  year = {2004},
  volume = {159},
  pages = {1-16},
  number = {1}
}

@ARTICLE{Tei06,
  author = {Teich, J.E. and Wallenius, H. and Wallenius, J. and Zaitsev, A.},
  title = {A multi-attribute e-auction mechanism for procurement: Theoretical
        foundations},
  journal = {European Journal of Operational Research},
  year = {2006},
  volume = {175},
  pages = {90-100},
  number = {1}
}

@INPROCEEDINGS{Tes02,
  author = {Tesauro, G.},
  title = {Efficient search techniques for multi-attribute bilateral negotiation
        strategies},
  booktitle = {Electronic Commerce, 2002. Proceedings. Third International Symposium
        on},
  year = {2002},
  pages = {30--36},
  organization = {IEEE},
  owner = {Mark},
  timestamp = {2013.02.02}
}

@ARTICLE{Thi98,
  author = {Ernest M. Thiessen and Daniel P. Loucks and Jery R. Stedinger},
  title = {Computer-Assisted Negotiations of Water Resources Conflicts},
  journal = {GDN},
  year = {1998},
  volume = {7},
  pages = {109-129},
  number = {2},
  keywords = {thiessen.pdf}
}

@ARTICLE{Tho05,
  author = {Thomas, Charles J. and Wilson, Bart J.},
  title = {Verifiable Offers and the Relationship Between Auctions and Multilateral
        Negotiations},
  journal = {The Economic Journal},
  year = {2005},
  volume = {115},
  pages = {1016-1031},
  number = {506}
}

@ARTICLE{Tho92,
  author = {Thomas, Kenneth W.},
  title = {Conflict and conflict management: Reflections and update},
  journal = {Journal of Organizational Behavior},
  year = {1992},
  volume = {13},
  pages = {265--274},
  number = {3},
  doi = {10.1002/job.4030130307},
  issn = {1099-1379},
  owner = {tim},
  publisher = {John Wiley \& Sons, Ltd.},
  timestamp = {2011.05.25},
  url = {http://dx.doi.org/10.1002/job.4030130307}
}

@BOOK{Tho00,
  title = {The Mind and heart of the negotiator},
  publisher = {Prentice Hall Press},
  year = {2000},
  author = {Thompson, Leigh},
  address = {Upper Saddle River, NJ, USA},
  edition = {3rd},
  isbn = {0-13-017964-7}
}

@MISC{Tho94,
  author = {Thomson, William},
  title = {Cooperative models of bargaining},
  year = {1994},
  publisher = {Elsevier Science B.V.}
}

@ARTICLE{Tip99,
  author = {Tipping, Michael E. and Bishop, Christopher M.},
  title = {Probabilistic Principal Component Analysis},
  journal = {Journal of the Royal Statistical Society: Series B (Statistical Methodology)},
  year = {1999},
  volume = {61},
  pages = {611--622},
  number = {3},
  doi = {10.1111/1467-9868.00196},
  issn = {1467-9868},
  keywords = {Density estimation, EM algorithm, Gaussian mixtures, Maximum likelihood,
        Principal component analysis, Probability model},
  publisher = {Blackwell Publishers Ltd.},
  url = {http://dx.doi.org/10.1111/1467-9868.00196}
}

@incollection{Tra08,
year={2008},
isbn={978-3-540-85482-1},
booktitle={Intelligent Virtual Agents},
volume={5208},
series={Lecture Notes in Computer Science},
editor={Prendinger, Helmut and Lester, James and Ishizuka, Mitsuru},
doi={10.1007/978-3-540-85483-8_12},
title={Multi-party, Multi-issue, Multi-strategy Negotiation for Multi-modal Virtual Agents},
url={http://dx.doi.org/10.1007/978-3-540-85483-8_12},
publisher={Springer Berlin Heidelberg},
author={Traum, David and Marsella, Stacy C. and Gratch, Jonathan and Lee, Jina and Hartholt, Arno},
pages={117-130}
}

@ARTICLE{Tri92,
  author = {Thomas M Tripp and Harris Sondak},
  title = {An evaluation of dependent variables in experimental negotiation     studies: Impasse rates and pareto efficiency },
  journal = {Organizational Behavior and Human Decision Processes },
  year = {1992},
  volume = {51},
  pages = {273 - 295},
  number = {2},
  note = {Decision Processes in Negotiation},
  doi = {http://dx.doi.org/10.1016/0749-5978(92)90014-X},
  issn = {0749-5978},
  url = {http://www.sciencedirect.com/science/article/pii/074959789290014X}
}

@INPROCEEDINGS{Tu00,
  author = {Tu, Tuan and Wolff, Eberhard and Lamersdorf, Winfried},
  title = {Genetic Algorithms for Automated Negotiations: A {FSM}-Based Application Approach},
  booktitle = {Proceedings of the 11th International Workshop on Database and Expert Systems Applications},
  year = {2000},
  series = {DEXA '00},
  pages={1029-1033}, 
  address = {Washington, DC, USA},
  publisher = {IEEE Computer Society},
  acmid = {790449},
  isbn = {0-7695-0680-1},
  owner = {Mark},
  timestamp = {2013.02.08}
}

@INPROCEEDINGS{Tu2000,
  author = {Tu, Tuan and Wolff, Eberhard and Lamersdorf, Winfried},
  title = {Genetic algorithms for automated negotiations: a {FSM}-based application approach},
  booktitle = {Database and Expert Systems Applications, 2000. Proceedings. 11th
        International Workshop on},
  year = {2000},
  pages = {1029-1033},
  abstract = {An approach to implement strategies for automated negotiations in
        electronic commerce applications is presented. It is based on genetic
        algorithms (GAs) that evolve FSMs (finite state machines). Each of
        these FSMs represents a negotiation strategy that competes against
        other strategies and is modified over time according to the outcome
        of this competition by using GA principles. The paper gives an overview
        of negotiating agents and work related to the paper. Then the application
        of genetic algorithms to FSMs is presented and relevant details on
        the implementation are given},
  doi = {10.1109/DEXA.2000.875153},
  issn = {1529-4188},
  keywords = {Internet;electronic commerce;finite state machines;genetic algorithms;negotiation
        support systems;software agents;FSM based application approach;GA
        principles;automated negotiations;electronic commerce applications;finite
        state machines;genetic algorithms;negotiating agents;negotiation
        strategy;Application software;Automata;Computer science;Concrete;Electronic
        commerce;Genetic algorithms;Genetic mutations;Humans;Mobile agents;Software
        agents}
}

@PHDTHESIS{Tyk10,
  author = {Tykhonov, D.},
  title = {Designing Generic and Efficient Negotation Strategies},
  school = {Delft University of Technology},
  year = {2010},
  owner = {Mark},
  timestamp = {2013.02.12}
}

@PHDTHESIS{Tykh10,
  author = {Dmytro Tykhonov},
  title = {Designing Generic and Efficient Negotiation Strategies},
  school = {Delft University of Technology},
  year = {2010},
  type = {Dissertation},
  address = {Delft, The Netherlands},
  isbn = {978-94-90818-02-9}
}

@article{Vah14,
        title = "An experimental study of software agent negotiations with humans",
        journal = "Decision Support Systems ",
        volume = "66",
        pages = "135 - 145",
        year = "2014",
        issn = "0167-9236",
        doi = "http://dx.doi.org/10.1016/j.dss.2014.06.009",
        url = "http://www.sciencedirect.com/science/article/pii/S0167923614001833",
        author = "Rustam M. Vahidov and Gregory E. Kersten and Raafat Saade",
        keywords = "Electronic negotiations",
        keywords = "Software agents",
        keywords = "Software human negotiations",
        keywords = "Experimental studies "
}

@ARTICLE{Van03,
  author = {David D.B. Bragt and Johannes A. La Poutr\'{e}},
  title = {Why agents for automated negotiations should be adaptive},
  journal = {Netnomics},
  year = {2003},
  volume = {5},
  pages = {101--118},
  number = {2},
  owner = {Mark},
  publisher = {Kluwer Academic Publishers},
  timestamp = {2013.01.27}
}

@ARTICLE{Van04,
  author = {Gerban A. Van Kleef and Carsten K.W. De Dreu and Antony S.R. Manstead},
  title = {The interpersonal effects of emotions in negotiations: a motivated information processing approach},
  journal = {Journal of Personality and Social Psychology},
  year = {2004},
  volume = {87},
  pages = {510},
  number = {4},
  owner = {Mark},
  publisher = {American Psychological Association},
  timestamp = {2012.01.08}
}

@ARTICLE{Vet09,
  author = {Rudolf Vetschera},
  title = {Learning about preferences in electronic negotiations - A volume-based
        measurement method},
  journal = {European Journal of Operational Research},
  year = {2009},
  volume = {194},
  pages = {452-463},
  number = {2},
  bibsource = {DBLP, http://dblp.uni-trier.de},
  ee = {http://dx.doi.org/10.1016/j.ejor.2007.12.016}
}

@INPROCEEDINGS{Vet07,
  author = {Vetsikas, Ioannis A. and Jennings, Nicholas R.},
  title = {Outperforming the competition in multi-unit sealed bid auctions},
  booktitle = {Proceedings of the 6th international joint conference on Autonomous
        agents and multiagent systems},
  year = {2007},
  series = {AAMAS '07},
  pages = {103:1--103:8},
  address = {New York, NY, USA},
  publisher = {ACM},
  acmid = {1329252},
  articleno = {103},
  doi = {10.1145/1329125.1329252},
  isbn = {978-81-904262-7-5},
  keywords = {bidding strategies, equilibrium analysis, game theory, revenue, simulation},
  location = {Honolulu, Hawaii},
  numpages = {8},
  url = {http://doi.acm.org/10.1145/1329125.1329252}
}

@ARTICLE{Vic61,
  author = {Vickrey, W.},
  title = {Counterspeculation, auctions, and competitive sealed tenders},
  journal = {Journal of Finance},
  year = {1961},
  volume = {16},
  pages = {8-37},
  number = {1}
}

@PHDTHESIS{Vis12Thesis,
  author = {Wietske Visser},
  title = {Qualitative Multi-Criteria Preference Representation and Reasoning},
  school = {Delft University of Technology},
  year = {2012},
  type = {Dissertation},
  address = {Delft, The Netherlands},
  isbn = {978-94-6186-078-1}
}

@ARTICLE{Vis12,
  author = {Wietske Visser and Koen V. Hindriks and Catholijn M. Jonker},
  title = {Argumentation-Based Qualitative Preference Modelling with Incomplete
        and Uncertain Information},
  journal = {Group Decision and Negotiation},
  year = {2012},
  volume = {21},
  pages = {99-127},
  abstract = {This paper presents an argumentation-based framework for the modelling
        of, and automated reasoning about multi-attribute preferences of
        a qualitative nature. The framework presents preferences according
        to the lexicographic ordering that is well-understood by humans.
        Preferences are derived in part from knowledge. Knowledge, however,
        may be incomplete or uncertain. The main contribution of the paper
        is that it shows how to reason about preferences when only incomplete
        or uncertain information is available.We propose a strategy that
        allows reasoning with incomplete information and discuss a number
        of strategies to handle uncertain information. It is shown how to
        extend the basic framework for modelling preferences to incorporate
        these strategies.},
  attachments = {http://ii.tudelft.nl/sites/default/files/visser\_hindriks\_jonker\_2012\_prefinal.pdf},
  doi = {10.1007/s10726-011-9274-2},
  keywords = {Argumentation, Incomplete information, Qualitative multi-attribute
        preferences, Uncertain information},
  owner = {Mark},
  timestamp = {2013.02.06},
  url = {http://www.springerlink.com/content/4158264484435056/}
}

@ARTICLE{Vul98,
  author = {Nir Vulkan and Nicholas R. Jennings},
  title = {Efficient mechanisms for the supply of services in multi-agent environments},
  journal = {Decision Support Systems},
  year = {2000},
  volume = {28},
  pages = {5 - 19},
  number = {1-2},
  doi = {10.1016/S0167-9236(99)00071-8},
  issn = {0167-9236},
  keywords = {Intelligent agents},
  owner = {Mark},
  timestamp = {2013.02.11},
  url = {http://www.sciencedirect.com/science/article/pii/S0167923699000718}
}

@ARTICLE{Vyt08,
  author = {Perukrishnen Vytelingum and Dave Cliff and Nicholas R. Jennings},
  title = {Strategic bidding in continuous double auctions },
  journal = {Artificial Intelligence },
  year = {2008},
  volume = {172},
  pages = {1700 - 1729},
  number = {14},
  abstract = {In this paper, we describe a novel bidding strategy that autonomous
        trading agents can use to participate in Continuous Double Auctions
        (CDAs). Our strategy is based on both short and long-term learning
        that allows such agents to adapt their bidding behaviour to be efficient
        in a wide variety of environments. For the short-term learning, the
        agent updates the aggressiveness of its bidding behaviour (more aggressive
        means it will trade off profit to improve its chance of transacting,
        less aggressive that it targets more profitable transactions and
        is willing to trade off its chance of transacting to achieve them)
        based on market information observed after any bid or ask appears
        in the market. The long-term learning then determines how this aggressiveness
        factor influences an agent's choice of which bids or asks to submit
        in the market, and is based on market information observed after
        every transaction (successfully matched bid and ask). The principal
        motivation for the short-term learning is to enable the agent to
        immediately respond to market fluctuations, while for the long-term
        learning it is to adapt to broader trends in the way in which the
        market demand and supply changes over time. We benchmark our strategy
        against the current state of the art (ZIP and GDX) and show that
        it outperforms these benchmarks in both static and dynamic environments.
        This is true both when the population is homogeneous (where the increase
        in efficiency is up to 5.2%) and heterogeneous (in which case there
        is a 0.85 probability of our strategy being adopted in a two-population
        evolutionary game theoretic analysis). },
  doi = {10.1016/j.artint.2008.06.001},
  issn = {0004-3702},
  keywords = {Continuous double auction},
  url = {http://www.sciencedirect.com/science/article/pii/S0004370208000787}
}

@ARTICLE{Wal08,
  author = {Wallenius, J. and Dyer, J. and Firshburn, P. and Steuer, R. and Zionts,
        S. and Deb, K.},
  title = {Multiple Criteria Decision Making and Multiattribute Utility Theory:
        Recent Accomplishments and What Lies Ahead},
  journal = {Management Science},
  year = {2008},
  volume = {54},
  pages = {1336-1349},
  abstract = {This paper is an update of a paper that five of us published in 1992.
        The areas of multiple criteria decision making (MCDM) and multiattribute
        utility theory (MAUT) continue to be active areas of management science
        research and application. This paper extends the history of these
        areas and discusses topics we believe to be important for the future
        of these fields.}
}

@BOOK{Wan95,
  title = {Kernel smoothing},
  publisher = {Chapman \& Hall/CRC},
  year = {1995},
  author = {Wand, M.P. and Jones, M.C.},
  owner = {---},
  timestamp = {2011.07.04}
}

@INPROCEEDINGS{Wang04,
  author = {Wang, L.M. and Huang, H.K. and Chai, Y.M.},
  title = {A learning-based multistage negotiation model},
  booktitle = {Proceedings of International
        Conference on Machine Learning and Cybernetics},
  year = {2004},
  volume = {1},
  pages = {140--145},
  organization = {IEEE},
  owner = {Mark},
  timestamp = {2013.01.25}
}

@ARTICLE{Wei79,
  author = {Weitzman, Martin L.},
  title = {Optimal search for the best alternative},
  journal = {Econometrica: Journal of the Econometric Society},
  year = {1979},
  pages = {641--654},
  publisher = {JSTOR},
  url = {http://scholar.harvard.edu/files/weitzman/files/optimalsearchbestalternative.pdf}
}

@ARTICLE{Wel05,
  author = {Wellman, Michael P. and Estelle, Joshua and Singh, Satinder and Vorobeychik,
        Yevgeniy and Kiekintveld, Christopher and Soni, Vishal},
  title = {STRATEGIC INTERACTIONS IN A SUPPLY CHAIN GAME},
  journal = {Computational Intelligence},
  year = {2005},
  volume = {21},
  pages = {1--26},
  number = {1},
  abstract = {The TAC 2003 supply-chain game presented automated trading agents
        with a challenging strategic problem. Embedded within a high-dimensional
        stochastic environment was a pivotal strategic decision about initial
        procurement of components. Early evidence suggested that the entrant
        field was headed toward a self-destructive, mutually unprofitable
        equilibrium. Our agent, Deep Maize, introduced a preemptive strategy
        designed to neutralize aggressive procurement, perturbing the field
        to a more profitable equilibrium; it worked. Not only did preemption
        improve Deep Maize's profitability, it improved profitability for
        the whole field. Whereas it is perhaps counterintuitive that action
        designed to prevent others from achieving their goals actually helps
        them, strategic analysis employing an empirical game-theoretic methodology
        verifies and provides insight about this outcome.},
  doi = {10.1111/j.0824-7935.2005.00263.x},
  issn = {1467-8640},
  keywords = {trading agents, supply chain management, strategic reasoning, empirical
        game theory},
  publisher = {Blackwell Publishing, Inc.},
  url = {http://dx.doi.org/10.1111/j.0824-7935.2005.00263.x}
}

@BOOK{Wel06,
  title = {Autonomous Bidding Agents: Strategies and Lessons from the Trading
        Agent Competition},
  publisher = {MIT Press},
  year = {2007},
  author = {Michael P. Wellman and Amy Greenwald and Peter Stone},
  address = {Cambridge MA, USA}
}

@ARTICLE{Tac01,
  author = {Michael P. Wellman and Peter R. Wurman and Kevin O'Malley and Roshan
        Bangera and Shou-de Lin and Daniel Reeves and William E. Walsh},
  title = {Designing the Market Game for a Trading Agent Competition},
  journal = {IEEE Internet Computing},
  year = {2001},
  volume = {5},
  pages = {43--51},
  number = {2},
  address = {Piscataway, NJ, USA},
  doi = {http://dx.doi.org/10.1109/4236.914647},
  issn = {1089-7801},
  owner = {tim},
  publisher = {IEEE Educational Activities Department},
  timestamp = {2010.06.03}
}

@PHDTHESIS{Wil12phdthesis,
  author = {Colin R. Williams},
  title = {Practical Strategies for Agent-Based Negotiation in Complex Environments},
  school = {University of Southampton},
  year = {2012},
  month = {Dec},
  abstract = {Agent-based negotiation, whereby the negotiation is automated by software
        programs, can be applied to many different negotiation situations,
        including negotiations between friends, businesses or countries.
        A key benefit of agent-based negotiation over human negotiation is
        that it can be used to negotiate effectively in complex negotiation
        environments, which consist of multiple negotiation issues, time
        constraints, and multiple unknown opponents. While automated negotiation
        has been an active area of research in the past twenty years, existing
        work has a number of limitations. Specifically, most of the existing
        literature has considered time constraints in terms of the number
        of rounds of negotiation that take place. In contrast, in this work
        we consider time constraints which are based on the amount of time
        that has elapsed. This requires a different approach, since the time
        spent computing the next action has an effect on the utility of the
        outcome, whereas the actual number of offers exchanged does not.
        In addition to these time constraints, in the complex negotiation
        environments which we consider, there are multiple negotiation issues,
        and we assume that the opponents? preferences over these issues and
        the behaviour of those opponents are unknown. Finally, in our environment
        there can be concurrent negotiations between many participants.
        
        Against this background, in this thesis we present the design of a
        range of practical negotiation strategies, the most advanced of which
        uses Gaussian process regression to coordinate its concession against
        its various opponents, whilst considering the behaviour of those
        opponents and the time constraints. In more detail, the strategy
        uses observations of the offers made by each opponent to predict
        the future concession of that opponent. By considering the discounting
        factor, it predicts the future time which maximises the utility of
        the offers, and we then use this in setting our rate of concession.
        Furthermore, we evaluate the negotiation agents that we have developed,
        which use our strategies, and show that, particularly in the more
        challenging scenarios, our most advanced strategy outperforms other
        state-of-the-art agents from the Automated Negotiating Agent Competition,
        which provides an international benchmark for this work. In more
        detail, our results show that, in one-to-one negotiation, in the
        highly discounted scenarios, our agent reaches outcomes which, on
        average, are 2.3\% higher than those of the next best agent.
        
        Furthermore, using empirical game theoretic analysis we show the robustness
        of our strategy in a variety of tournament settings. This analysis
        shows that, in the highly discounted scenarios, no agent can benefit
        by choosing a different strategy (taken from the top four strategies
        in that setting) than ours. Finally, in the many-to-many negotiations,
        we show how our strategy is particularly effective in highly competitive
        scenarios, where it outperforms the state-of-the-art many-to-many
        negotiation strategy by up to 45\%.},
  owner = {Mark},
  timestamp = {2013.06.05},
  url = {http://eprints.soton.ac.uk/348190/}
}

@INCOLLECTION{ANAC2012,
  author={Williams, Colin R. and Robu, Valentin and Gerding, Enrico H. and Jennings, Nicholas R.},
  title = {An overview of the results and insights from the third automated negotiating agents competition {(ANAC 2012)}},
  booktitle = {Novel Insights in Agent-based Complex Automated Negotiation},
  publisher = {Springer, Japan},
  year = {2014},
editor={Marsa-Maestre, Ivan and Lopez-Carmona, Miguel A. and Ito, Takayuki and Zhang, Minjie and Bai, Quan and Fujita, Katsuhide},
  volume = {535},
  series = {Studies in Computational Intelligence},
  pages = {151-162},
  url={http://dx.doi.org/10.1007/978-4-431-54758-7_9},
  doi={10.1007/978-4-431-54758-7_9},
  keywords={AI competitions; Automated negotiation; Multi-agent systems},
  isbn = {978-4-431-54757-0}
}

@INCOLLECTION{ANAC2012OMACAgent,
  author = {Chen, S. and Weiss, G.},
  title = {{OMAC}: a discrete wavelet transformation based negotiation agent},
  booktitle = {Novel Insights in Agent-based Complex Automated Negotiation},
  publisher = {Springer, Japan},
  year = {2014},
  editor = {Marsa-Maestre, I. and Lopez-Carmona, M.A. and Ito, T. and Zhang,
        M. and Bai, Q. and Fujita, K.},
  volume = {535},
  series = {Studies in Computational Intelligence},
  pages = {187-196},
  isbn = {978-4-431-54757-0}
}

@INCOLLECTION{ANAC2012TheNegotiatorReloaded,
  author = {Alexander S.Y. Dirkzwager and Mark J.C. Hendrikx},
  title = {An Adaptive Negotiation Strategy for Real-Time Bilateral Negotiations},
  booktitle = {Novel Insights in Agent-based Complex Automated Negotiation},
  publisher = {Springer, Japan},
  year = {2014},
  editor = {Marsa-Maestre, I. and Lopez-Carmona, M.A. and Ito, T. and Zhang,
        M. and Bai, Q. and Fujita, K.},
  volume = {535},
  series = {Studies in Computational Intelligence},
  pages = {163-170},
  isbn = {978-4-431-54757-0}
}


@article{Hao14,
title = "An efficient and robust negotiating strategy in bilateral negotiations over multiple items",
journal = "Engineering Applications of Artificial Intelligence",
volume = "34",
number = "0",
pages = "45 - 57",
year = "2014",
issn = "0952-1976",
doi = "http://dx.doi.org/10.1016/j.engappai.2014.05.008",
url = "http://www.sciencedirect.com/science/article/pii/S0952197614001067",
author = {Jianye Hao and Songzheng Song and {Ho-fung} Leung and Zhong Ming},
keywords = "Bilateral negotiation",
abstract = "Abstract Multi-item negotiations surround our daily life and usually involve two parties that share common or conflicting interests. Effective automated negotiation techniques should enable the agents to adaptively adjust their behaviors depending on the characteristics of their negotiating partners and negotiation scenarios. This is complicated by the fact that the negotiation agents are usually unwilling to reveal their information (strategies and preferences) to avoid being exploited during negotiation. In this paper, we propose an adaptive negotiation strategy, called ABiNeS, which can make effective negotiations against different types of negotiating partners. The {ABiNeS} strategy employs the non-exploitation point to adaptively adjust the appropriate time to stop exploiting the negotiating partner and also predicts the optimal offer for the negotiating partner based on the reinforcement-learning based approach. Simulation results show that the {ABiNeS} strategy can perform more efficient exploitations against different types of negotiating partners, and thus achieve higher overall payoffs compared with the state-of-the-art strategies under negotiation tournaments. We also provide a detailed analysis of why the {ABiNeS} strategy can negotiate more efficiently compared with other existing state-of-the-art negotiation strategies focusing on two major components. Lastly, we propose adopting the single-agent best deviation principle to analyze the robustness of different negotiation strategies based on model checking techniques. Through our analysis, the {ABiNeS} strategy is shown to be very robust against other state-of-the-art strategies under different negotiation contexts. "
}




@INCOLLECTION{ANAC2012CUHKAgent,
author={Hao, Jianye and Leung, {Ho-fung}},
  title = {{CUHK} agent: an adaptive negotiation strategy for bilateral negotiations over multiple items},
  booktitle = {Novel Insights in Agent-based Complex Automated Negotiation},
  publisher = {Springer, Japan},
  year = {2014},
editor={Marsa-Maestre, Ivan and Lopez-Carmona, Miguel A. and Ito, Takayuki and Zhang, Minjie and Bai, Quan and Fujita, Katsuhide},
  doi={10.1007/978-4-431-54758-7_11},
  volume = {535},
  series = {Studies in Computational Intelligence},
pages={171-179},
  isbn = {978-4-431-54757-0}
}

@INPROCEEDINGS{ANAC2012CUHKAgentIAT,
  author = {Hao, Jianye and Leung, {Ho-fung}},
  title = {{ABiNeS}: An Adaptive Bilateral Negotiating Strategy over Multiple Items},
  booktitle = {Proceedings of the The 2012 IEEE/WIC/ACM International Joint Conferences on Web Intelligence and Intelligent Agent Technology},
  year = {2012},
  month={Dec},
  volume={2}, 
  series = {WI-IAT '12},
  pages = {95--102},
  address = {Washington, DC, USA},
  publisher = {IEEE Computer Society},
  acmid = {2457744},
  doi = {10.1109/WI-IAT.2012.72},
  isbn = {978-0-7695-4880-7},
  numpages = {8},
  owner = {Mark},
  timestamp = {2013.06.03},
  url = {http://dx.doi.org/10.1109/WI-IAT.2012.72}
}

@INCOLLECTION{ANAC2012MetaAgent,
  author = {Ilany, L. and Gal, Y. (K.)},
  title = {The simple-meta agent},
  booktitle = {Novel Insights in Agent-based Complex Automated Negotiation},
  publisher = {Springer, Japan},
  year = {2014},
  editor = {Marsa-Maestre, I. and Lopez-Carmona, M.A. and Ito, T. and Zhang,
        M. and Bai, Q. and Fujita, K.},
  volume = {535},
  series = {Studies in Computational Intelligence},
  pages = {197-200},
  isbn = {978-4-431-54757-0}
}

@INPROCEEDINGS{ANAC2012MetaAgentAAAI,
  author = {Litan Ilany and Yakov Gal},
  title = {Algorithm Selection in Bilateral Negotiation},
  booktitle = {Proceedings of the Twenty-Seventh AAAI Conference on Artificial Intelligence     (AAAI 2013)},
  year = {2013},
  abstract = {Despite the abundance of strategies in the literature on repeated
        negotiation under incomplete information, there is no single negotiation
        strategy that is optimal for all possible set- tings. Thus, agent
        designers face an algorithm selection problem which negotiation strategy
        to choose when facing a new negotiation. Our approach to this problem
        is to pre- dict the performance of different strategies based on
        structural features of the domain and to select the negotiation strategy
        that is predicted to be most successful using a meta-agent. This
        agent was able to outperform all of the finalists to the recent Automated
        Negotiation Agent Competition (ANAC). Our results have insights for
        agent-designers, demonstrating that a little learning goes a long
        way, despite the inherent uncertainty associated with negotiation
        under incomplete information.},
  conference = {AAAI Workshops},
  keywords = {negotiation, algorithm selection, decision-making},
  url = {http://www.aaai.org/ocs/index.php/WS/AAAIW13/paper/view/7111/6687}
}

@INCOLLECTION{ANAC2012AgentMR,
  author = {Morii, S. and Ito, T.},
  title = {{AgentMR}: concession strategy based on heuristic for automated negotiating agents},
  booktitle = {Novel Insights in Agent-based Complex Automated Negotiation},
  publisher = {Springer, Japan},
  year = {2014},
  editor = {Marsa-Maestre, I. and Lopez-Carmona, M.A. and Ito, T. and Zhang,
        M. and Bai, Q. and Fujita, K.},
  volume = {535},
  series = {Studies in Computational Intelligence},
  pages = {181-186},
  isbn = {978-4-431-54757-0}
}

@Inbook{ANAC2013,
author="(Ya'akov) Gal, Kobi
and Ilany, Litan",
editor="Fujita, Katsuhide
and Ito, Takayuki
and Zhang, Minjie
and Robu, Valentin",
chapter="The Fourth Automated Negotiation Competition",
title="Next Frontier in Agent-based Complex Automated Negotiation",
year="2015",
publisher="Springer Japan",
address="Tokyo",
pages="129--136",
isbn="978-4-431-55525-4",
doi="10.1007/978-4-431-55525-4_8",
url="http://dx.doi.org/10.1007/978-4-431-55525-4_8"
}

@misc{ANAC2013all,
  title={The forth international automated negotiating agents competition (ANAC2013)},
  author={Gal, K and Ito, T and Jonker, C and Kraus, S and Hindriks, K and Lin, R and Baarslag, T},
  year={2013}
}

@INCOLLECTION{ANAC2013AgentMRK2,
  author = {Morii, Shota and Ito, Takayuki},
  title = {Agent's Strategy in Multiple-Issue Negotiation Competition and Analysis of Result},
  booktitle = {PRIMA 2013: Principles and Practice of Multi-Agent Systems},
  publisher = {Springer Berlin Heidelberg},
  year = {2013},
  editor = {Boella, Guido and Elkind, Edith and Savarimuthu, Bastin Tony Roy
        and Dignum, Frank and Purvis, Martin K.},
  volume = {8291},
  series = {Lecture Notes in Computer Science},
  pages = {486-493},
  doi = {10.1007/978-3-642-44927-7_38},
  isbn = {978-3-642-44926-0},
  keywords = {Multi-Agent System; Multi-issue Negotiation; Automated Negotiation Competition},
  url = {http://dx.doi.org/10.1007/978-3-642-44927-7\_38}
}

@Inbook{ANAC2014BraveCat,
author="Zafari, Farhad and Nassiri-Mofakham, Faria",
editor="Fukuta, Naoki and Ito, Takayuki and Zhang, Minjie and Fujita, Katsuhide and Robu, Valentin",
chapter="BraveCat: Iterative Deepening Distance-Based Opponent Modeling and Hybrid Bidding in Nonlinear Ultra Large Bilateral Multi Issue Negotiation Domains",
title="Recent Advances in Agent-based Complex Automated Negotiation",
year="2016",
publisher="Springer International Publishing",
address="Cham",
pages="285--293",
isbn="978-3-319-30307-9",
doi="10.1007/978-3-319-30307-9_21",
url="http://dx.doi.org/10.1007/978-3-319-30307-9_21"
}

@Inbook{ANAC2014AgentYK,
author="Kadono, Yoshiaki",
editor="Fukuta, Naoki and Ito, Takayuki and Zhang, Minjie and Fujita, Katsuhide and Robu, Valentin",
chapter="Agent YK: An Efficient Estimation of Opponent's Intention with Stepped Limited Concessions",
title="Recent Advances in Agent-based Complex Automated Negotiation",
year="2016",
publisher="Springer International Publishing",
address="Cham",
pages="279--283",
isbn="978-3-319-30307-9",
doi="10.1007/978-3-319-30307-9_20",
url="http://dx.doi.org/10.1007/978-3-319-30307-9_20"
}

@Inbook{ANAC2014Group2Agent,
author="Sz{\"o}ll{\H{o}}si-Nagy, B{\'a}lint and Festen, David and Skar{\.{z}}y{\'{n}}ska, Marta M.",
editor="Fukuta, Naoki and Ito, Takayuki and Zhang, Minjie and Fujita, Katsuhide and Robu, Valentin",
chapter="A Greedy Coordinate Descent Algorithm for High-Dimensional Nonlinear Negotiation",
title="Recent Advances in Agent-based Complex Automated Negotiation",
year="2016",
publisher="Springer International Publishing",
address="Cham",
pages="249--260",
isbn="978-3-319-30307-9",
doi="10.1007/978-3-319-30307-9_17",
url="http://dx.doi.org/10.1007/978-3-319-30307-9_17"
}

@Inbook{ANAC2015Buyog,
author="Sosale, Bhargav
and Satish, Swarup
and An, Bo",
editor="Fujita, Katsuhide
and Bai, Quan
and Ito, Takayuki
and Zhang, Minjie
and Ren, Fenghui
and Aydo{\u{g}}an, Reyhan
and Hadfi, Rafik",
title="Agent Buyog: A Negotiation Strategy for Tri-Party Multi Issue Negotiation",
bookTitle="Modern Approaches to Agent-based Complex Automated Negotiation",
year="2017",
publisher="Springer International Publishing",
address="Cham",
pages="191--199",
isbn="978-3-319-51563-2",
doi="10.1007/978-3-319-51563-2_14",
url="http://dx.doi.org/10.1007/978-3-319-51563-2_14"
}

@Inbook{ANAC2015Pokerface,
author="Peperkamp, J. B.
and Smit, V. J.",
editor="Fujita, Katsuhide
and Bai, Quan
and Ito, Takayuki
and Zhang, Minjie
and Ren, Fenghui
and Aydo{\u{g}}an, Reyhan
and Hadfi, Rafik",
title="Pokerface: The Pokerface Strategy for Multiparty Negotiation",
bookTitle="Modern Approaches to Agent-based Complex Automated Negotiation",
year="2017",
publisher="Springer International Publishing",
address="Cham",
pages="213--218",
isbn="978-3-319-51563-2",
doi="10.1007/978-3-319-51563-2_16",
url="http://dx.doi.org/10.1007/978-3-319-51563-2_16"
}

@Inbook{ANAC2015Phoenix,
author="Lam, Max W. Y.
and Leung, Ho-fung",
editor="Fujita, Katsuhide
and Bai, Quan
and Ito, Takayuki
and Zhang, Minjie
and Ren, Fenghui
and Aydo{\u{g}}an, Reyhan
and Hadfi, Rafik",
title="Phoenix: A Threshold Function Based Negotiation Strategy Using Gaussian Process Regression and Distance-Based Pareto Frontier Approximation",
bookTitle="Modern Approaches to Agent-based Complex Automated Negotiation",
year="2017",
publisher="Springer International Publishing",
address="Cham",
pages="201--212",
isbn="978-3-319-51563-2",
doi="10.1007/978-3-319-51563-2_15",
url="http://dx.doi.org/10.1007/978-3-319-51563-2_15"
}

@Inbook{ANAC2015JohnnyBlack,
author="Yucel, Osman
and Hoffman, Jon
and Sen, Sandip",
editor="Fujita, Katsuhide
and Bai, Quan
and Ito, Takayuki
and Zhang, Minjie
and Ren, Fenghui
and Aydo{\u{g}}an, Reyhan
and Hadfi, Rafik",
title="Jonny Black: A Mediating Approach to Multilateral Negotiations",
bookTitle="Modern Approaches to Agent-based Complex Automated Negotiation",
year="2017",
publisher="Springer International Publishing",
address="Cham",
pages="231--238",
isbn="978-3-319-51563-2",
doi="10.1007/978-3-319-51563-2_18",
url="http://dx.doi.org/10.1007/978-3-319-51563-2_18"
}

@Inbook{ANAC2015SPGP,
author="Chen, Siqi
and Hao, Jianye
and Zhou, Shuang
and Weiss, Gerhard",
editor="Fujita, Katsuhide
and Bai, Quan
and Ito, Takayuki
and Zhang, Minjie
and Ren, Fenghui
and Aydo{\u{g}}an, Reyhan
and Hadfi, Rafik",
title="Negotiating with Unknown Opponents Toward Multi-lateral Agreement in Real-Time Domains",
bookTitle="Modern Approaches to Agent-based Complex Automated Negotiation",
year="2017",
publisher="Springer International Publishing",
address="Cham",
pages="219--229",
isbn="978-3-319-51563-2",
doi="10.1007/978-3-319-51563-2_17",
url="http://dx.doi.org/10.1007/978-3-319-51563-2_17"
}

@Inbook{ANAC2015DependencyBased,
author="Mori, Akiyuki
and Morii, Shota
and Ito, Takayuki",
editor="Fujita, Katsuhide
and Bai, Quan
and Ito, Takayuki
and Zhang, Minjie
and Ren, Fenghui
and Aydo{\u{g}}an, Reyhan
and Hadfi, Rafik",
title="A Dependency-Based Mediation Mechanism for Complex Negotiations",
bookTitle="Modern Approaches to Agent-based Complex Automated Negotiation",
year="2017",
publisher="Springer International Publishing",
address="Cham",
pages="51--66",
isbn="978-3-319-51563-2",
doi="10.1007/978-3-319-51563-2_4",
url="http://dx.doi.org/10.1007/978-3-319-51563-2_4"
}

@Inbook{ANAC2015SPEA2,
author="Kakimoto, Shinji
and Fujita, Katsuhide",
editor="Fujita, Katsuhide
and Bai, Quan
and Ito, Takayuki
and Zhang, Minjie
and Ren, Fenghui
and Aydo{\u{g}}an, Reyhan
and Hadfi, Rafik",
title="Compromising Strategy Considering Interdependencies of Issues for Multi-issue Closed Nonlinear Negotiations",
bookTitle="Modern Approaches to Agent-based Complex Automated Negotiation",
year="2017",
publisher="Springer International Publishing",
address="Cham",
pages="85--100",
isbn="978-3-319-51563-2",
doi="10.1007/978-3-319-51563-2_6",
url="http://dx.doi.org/10.1007/978-3-319-51563-2_6"
}

@Inbook{ANAC2015Atlas3,
author="Mori, Akiyuki
and Ito, Takayuki",
editor="Fujita, Katsuhide
and Bai, Quan
and Ito, Takayuki
and Zhang, Minjie
and Ren, Fenghui
and Aydo{\u{g}}an, Reyhan
and Hadfi, Rafik",
title="Atlas3: A Negotiating Agent Based on Expecting Lower Limit of Concession Function",
bookTitle="Modern Approaches to Agent-based Complex Automated Negotiation",
year="2017",
publisher="Springer International Publishing",
address="Cham",
pages="169--173",
isbn="978-3-319-51563-2",
doi="10.1007/978-3-319-51563-2_11",
url="http://dx.doi.org/10.1007/978-3-319-51563-2_11"
}

@Inbook{ANAC2015ParsAgent,
author="Khosravimehr, Zahra
and Nassiri-Mofakham, Faria",
editor="Fujita, Katsuhide
and Bai, Quan
and Ito, Takayuki
and Zhang, Minjie
and Ren, Fenghui
and Aydo{\u{g}}an, Reyhan
and Hadfi, Rafik",
title="Pars Agent: Hybrid Time-Dependent, Random and Frequency-Based Bidding and Acceptance Strategies in Multilateral Negotiations",
bookTitle="Modern Approaches to Agent-based Complex Automated Negotiation",
year="2017",
publisher="Springer International Publishing",
address="Cham",
pages="175--183",
isbn="978-3-319-51563-2",
doi="10.1007/978-3-319-51563-2_12",
url="http://dx.doi.org/10.1007/978-3-319-51563-2_12"
}

@INPROCEEDINGS{Wil12,
  author = {Colin R. Williams and Valentin Robu and Enrico H. Gerding and Nicholas R. Jennings},
  title = {Towards a Platform for Concurrent Negotiations in Complex Domain},
  booktitle = {Proceedings of The Fifth International Workshop on Agent-based Complex
        Automated Negotiations (ACAN 2012)},
  year = {2012}
}

@INPROCEEDINGS{ANAC2010WilExt,
  author = {Colin R. Williams and Valentin Robu and Enrico H. Gerding and Nicholas
        R. Jennings},
  title = {IAMhaggler: A Negotiation Agent for Complex Environments},
  booktitle = {New Trends in Agent-based Complex Automated Negotiations},
  series={Studies in Computational Intelligence},
  year = {2012},
  doi={10.1007/978-3-642-24696-8_10},
  editor = {Takayuki Ito and Minjie Zhang and Valentin Robu and Shaheen Fatima
        and Tokuro Matsuo},
  pages = {151-158},
  address = {Berlin, Heidelberg},
  publisher = {Springer-Verlag},
  isbn = {978-3-642-24695-1},
  owner = {tim},
  url = {http://eprints.soton.ac.uk/271662/1/acan2010.pdf}
}

@INCOLLECTION{ANAC2011Wil,
  author = {Williams, Colin R. and Robu, Valentin and Gerding, Enrico H. and
        Jennings, Nicholas R.},
  title = {IAMhaggler2011: A Gaussian Process Regression Based Negotiation Agent},
  booktitle = {Complex Automated Negotiations: Theories, Models, and Software Competitions},
  publisher = {Springer Berlin Heidelberg},
  year = {2013},
  editor = {Ito, Takayuki and Zhang, Minjie and Robu, Valentin and Matsuo, Tokuro},
  volume = {435},
  series = {Studies in Computational Intelligence},
  pages = {209-212},
  doi = {10.1007/978-3-642-30737-9\_14},
  isbn = {978-3-642-30736-2},
  url = {http://dx.doi.org/10.1007/978-3-642-30737-9\_14}
}

@INCOLLECTION{ANAC2011Wilshort,
  author = {Williams, Colin R. and Robu, Valentin and Gerding, Enrico H. and
        Jennings, Nicholas R.},
  title = {IAMhaggler2011: A Gaussian Process Regression Based Negotiation Agent},
  booktitle = {Complex Automated Negotiations: Theories, Models, and Software Competitions},
  publisher = {Springer Berlin Heidelberg},
  year = {2013},
  pages = {209-212},
  doi = {10.1007/978-3-642-30737-9\_14},
  isbn = {978-3-642-30736-2},
  url = {http://dx.doi.org/10.1007/978-3-642-30737-9\_14}
}

@ARTICLE{ANAC2010Wil,
  author = {Colin R. Williams and Valentin Robu and Enrico H. Gerding and Nicholas
        R. Jennings},
  title = {IAMhaggler: A Negotiation Agent for Complex Environments},
  journal = {This volume},
  year = {2012},
  pages = {151-158}
}

@INPROCEEDINGS{ANAC2010WilExtshort,
  author = {Colin R. Williams and Valentin Robu and Enrico H. Gerding and Nicholas
        R. Jennings},
  title = {IAMhaggler: A Negotiation Agent for Complex Environments},
  booktitle = {New Trends in Agent-based Complex Automated Negotiations},
  year = {2012},
  pages = {151-158},
  address = {Berlin, Heidelberg},
  publisher = {Springer-Verlag},
  isbn = {978-3-642-24695-1},
  owner = {tim},
  url = {http://eprints.soton.ac.uk/271662/1/acan2010.pdf}
}

@INPROCEEDINGS{ANAC2010WilExtshorter,
  author = {Colin R. Williams and Valentin Robu and Enrico H. Gerding and Nicholas
        R. Jennings},
  title = {IAMhaggler: A Negotiation Agent for Complex Environments},
  booktitle = {New Trends in Agent-based Complex Automated Negotiations},
  year = {2012},
  pages = {151-158},
  publisher = {Springer-Verlag},
  isbn = {978-3-642-24695-1},
  owner = {tim},
  timestamp = {2013.04.20}
}

@INPROCEEDINGS{Wil12Concurrently,
  author = {Colin R. Williams and Valentin Robu and Enrico H. Gerding and Nicholas R. Jennings},
  title = {Negotiating Concurrently with Unknown Opponents in Complex, Real-Time Domains},
  booktitle = {20th European Conference on Artificial Intelligence},
  year = {2012},
  volume = {242},
  pages = {834--839},
  month = {Aug},
  abstract = {We propose a novel strategy to enable autonomous agents to negotiate
        concurrently with multiple, unknown opponents in real-time, over
        complex multi-issue domains. We formalise our strategy as an optimisation
        problem, in which decisions are based on probabilistic information
        about the opponents' strategies acquired during negotiation. In doing
        so, we develop the first principled approach that enables the coordination
        of multiple, concurrent negotiation threads for practical negotiation
        settings. Furthermore, we validate our strategy using the agents
        and domains developed for the International Automated Negotiating
        Agents Competition (ANAC), and we benchmark our strategy against
        the state-of-the-art. We find that our approach significantly outperforms
        existing approaches, and this difference improves even further as
        the number of available negotiation opponents and the complexity
        of the negotiation domain increases.},
  keywords = {Automated Negotiation, Multi-issue Negotiation, Concurrent Negotiation},
  owner = {Mark},
  timestamp = {2013.02.11},
  url = {http://eprints.soton.ac.uk/339064/}
}

@INPROCEEDINGS{Wil11,
  author = {Williams, Colin R. and Robu, Valentin and Gerding, Enrico H. and Jennings, Nicholas R.},
  title = {Using Gaussian processes to optimise concession in complex negotiations against unknown opponents},
  booktitle = {Proceedings of the Twenty-Second International Joint Conference on Artificial Intelligence},
        volume={1},
  year = {2011},
  series = {IJCAI'11},
  pages = {432--438},
  publisher = {AAAI Press},
  acmid = {2283467},
  doi = {10.5591/978-1-57735-516-8/IJCAI11-080},
  isbn = {978-1-57735-513-7},
  location = {Barcelona, Catalonia, Spain},
  numpages = {7},
  url = {http://dx.doi.org/10.5591/978-1-57735-516-8/IJCAI11-080}
}

@INPROCEEDINGS{Wil11short,
  author = {Colin R. Williams and Valentin Robu and Enrico H. Gerding and Nicholas R. Jennings},
  title = {Using Gaussian Processes to Optimise Concession in Complex Negotiations against Unknown Opponents},
  booktitle = {Proceedings of the 22nd International Joint Conference on Artificial     Intelligence},
  year = {2011},
  month = {Jan},
  publisher = {AAAI Press},
  abstract = {In multi-issue automated negotiation against unknown opponents, a
        key part of effective negotiation is the choice of concession strategy.
        In this paper, we develop a principled concession strategy, based
        on Gaussian processes predicting the opponent's future behaviour.
        We then use this to set the agent's concession rate dynamically during
        a single negotiation session. We analyse the performance of our strategy
        and show that it outperforms the state-of-the-art negotiating agents
        from the 2010 Automated Negotiating Agents Competition, in both a
        tournament setting and in self-play, across a variety of negotiation
        domains.},
  owner = {Mark},
  timestamp = {2013.04.20}
}

@ARTICLE{Wit86,
  author = {Wittman, Donald},
  title = {Final-Offer Arbitration},
  journal = {Management Science},
  year = {1986},
  volume = {32},
  pages = {1551--1561},
  number = {12},
  abstract = {In final-offer arbitration the two parties to a dispute submit final
        offers to an arbitrator. The arbitrator then chooses as the binding
        solution that offer which is closest to his own view of the appropriate
        outcome. Because the disputants are imperfectly informed about the
        arbitrator's preferences, final-offer arbitration can be modeled
        as a game of imperfect information. Interesting questions arise concerning
        the nature of the optimal strategies and how they are affected by
        different characteristics of the arbitrator and the disputants. We
        provide conditions for an equilibrium to exist in a final-offer arbitration
        game when there are k issues, the probability function is not specified
        and the disputants are either risk averse or risk neutral. Furthermore,
        the players may have differing beliefs about the arbitrator's probability
        function. We demonstrate that increased risk aversion by one of the
        parties will result in both players choosing positions farther away
        from the more risk averse party. We also discover the affect of bias
        (as well as the effect of increased sensitivity) by the arbitrator
        on the positions taken by the players.},
  copyright = {Copyright 1986 INFORMS},
  issn = {00251909},
  jstor_articletype = {primary article},
  jstor_formatteddate = {Dec., 1986},
  owner = {tim},
  publisher = {INFORMS},
  timestamp = {2010.07.20},
  url = {http://www.jstor.org/stable/2631829}
}

@INCOLLECTION{Wu13,
  author = {Mengxiao Wu and Mathijs de Weerdt and Johannes A. La Poutr\'{e}},
  title = {Acceptance Strategies for Maximizing Agent Profits in Online Scheduling},
  booktitle = {Agent-Mediated Electronic Commerce. Designing Trading Strategies and Mechanisms for Electronic Markets},
  publisher = {Springer Berlin Heidelberg},
  year = {2013},
  editor = {David, Esther and Robu, Valentin and Shehory, Onn and Stein, Sebastian
        and Symeonidis, Andreas},
  volume = {119},
  series = {Lecture Notes in Business Information Processing},
  pages = {115-128},
  doi = {10.1007/978-3-642-34889-1\_9},
  isbn = {978-3-642-34888-4},
  keywords = {Online decisions; Resource allocation; Admission control},
  url = {http://dx.doi.org/10.1007/978-3-642-34889-1\_9}
}

@ARTICLE{You93,
  author = {Young, H Peyton},
  title = {The evolution of conventions},
  journal = {Econometrica: Journal of the Econometric Society},
  year = {1993},
  volume = {61},
  pages = {57--84},
  number = {1},
  publisher = {JSTOR}
}

@INCOLLECTION{Yu13,
  author = {Yu, Chao and Ren, Fenghui and Zhang, Minjie},
  title = {An Adaptive Bilateral Negotiation Model Based on Bayesian Learning},
  booktitle = {Complex Automated Negotiations: Theories, Models, and Software Competitions},
  publisher = {Springer Berlin Heidelberg},
  year = {2013},
  editor = {Ito, Takayuki and Zhang, Minjie and Robu, Valentin and Matsuo, Tokuro},
  volume = {435},
  series = {Studies in Computational Intelligence},
  pages = {75-93},
  doi = {10.1007/978-3-642-30737-9\_5},
  isbn = {978-3-642-30736-2},
  owner = {Mark},
  timestamp = {2013.05.28},
  url = {http://dx.doi.org/10.1007/978-3-642-30737-9\_5}
}

@INPROCEEDINGS{Yua07,
  author = {Yuan, Yong and Liang, Yong-quan},
  title = {Multi-Issue Negotiation Research Based On Niched Co-evolutionary
        Genetic Algorithm},
  booktitle = {Proceedings of the Eighth ACIS International Conference on Software
        Engineering, Artificial Intelligence, Networking, and Parallel/Distributed
        Computing},
        volume = {1},
  year = {2007},
  series = {SNPD '07},
  pages = {564--569},
  address = {Washington, DC, USA},
  publisher = {IEEE Computer Society},
  acmid = {1307648},
  isbn = {0-7695-2909-7},
  numpages = {6},
  owner = {Mark},
  timestamp = {2013.02.08}
}

@ARTICLE{Zac08,
  author = {Frederik Zachariassen},
  title = {Negotiation strategies in supply chain management},
  journal = {International Journal of Physical Distribution and Logistics Management},
  year = {2008},
  volume = {38},
  pages = {764--781},
  doi = {10.1108/09600030810926484},
  masid = {19963448},
  owner = {tim}
}

@article{Zen98,
title = "Bayesian learning in negotiation ",
journal = "International Journal of Human-Computer Studies ",
volume = "48",
number = "1",
pages = "125 - 141",
year = "1998",
issn = "1071-5819",
doi = "http://dx.doi.org/10.1006/ijhc.1997.0164",
url = "http://www.sciencedirect.com/science/article/pii/S1071581997901646",
author = {Dajun Zeng and Katia P. Sycara},
abstract = "Negotiation has been extensively discussed in game-theoretic, economic and management science literatures for decades. Recent growing interest in autonomous interacting software agents and their potential application in areas such as electronic commerce has give increased importance to automated negotiation. Evidence both from theoretical analysis and from observations of human interactions suggests that if decision makers can somehow take into consideration what other agents are thinking and furthermore learn during their interactions how other agents behave, their payoff might increase. In this paper, we propose a sequential decision-making model of negotiation, called Bazaar. It provides an adaptive, multi-issue negotiation model capable of exhibiting a rich set of negotiation behaviors. Within the proposed negotiation framework, we model learning as a Bayesian belief update process. In this paper, we present both theoretical analysis and initial experimental results showing that learning is beneficial in the sequential negotiation model. "
}

@inproceedings{Zen97,
 author = {Zeng, Dajun and Sycara, Katia P.},
 title = {Benefits of Learning in Negotiation},
 booktitle = {Proceedings of the Fourteenth National Conference on Artificial Intelligence and Ninth Conference on Innovative Applications of Artificial Intelligence},
 series = {AAAI'97/IAAI'97},
 year = {1997},
 isbn = {0-262-51095-2},
 location = {Providence, Rhode Island},
 pages = {36--41},
 numpages = {6},
 url = {http://dl.acm.org/citation.cfm?id=1867406.1867412},
 acmid = {1867412},
 publisher = {AAAI Press},
} 


@ARTICLE{Zen97Learn,
  author = {Dajun Zeng and Katia P. Sycara},
  title = {How can an agent learn to negotiate?},
  journal = {Intelligent Agents III Agent Theories, Architectures, and Languages},
  year = {1997},
  volume = {1193},
  pages = {233--244},
  owner = {Mark},
  publisher = {Springer},
  timestamp = {2013.02.09}
}

@INPROCEEDINGS{Zha08, 
author={Mingwen Zhang and Zhongfu Tan and Jianbao Zhao and Li Li}, 
booktitle={Intelligent Information Technology Application Workshops, 2008. IITAW '08. International Symposium on}, 
title={A Bayesian Learning Model in the Agent-based Bilateral Negotiation between the Coal Producers and Electric Power Generators}, 
year={2008}, 
month={Dec}, 
pages={859-862}, 
keywords={learning (artificial intelligence);multi-agent systems;power engineering computing;power generation economics;Bayesian learning model;agent-based bilateral negotiation;coal producers;electric coal bilateral contracts;electric power generators;Bayesian methods;Business;Companies;Energy management;Information technology;Intelligent agent;Internet;Power generation;Technology management;Waste materials;Agent;Bayesian Learning;Electric price}, 
doi={10.1109/IITA.Workshops.2008.144}
}

@INPROCEEDINGS{Zha04,
  author = {Zhang, Sheng and Ye, Song and Makedon, Fillia and Ford, James},
  title = {A hybrid negotiation strategy mechanism in an automated negotiation
        system},
  booktitle = {Proceedings of the 5th ACM conference on Electronic commerce},
  year = {2004},
  series = {EC '04},
  pages = {256--257},
  address = {New York, NY, USA},
  publisher = {ACM},
  acmid = {988821},
  isbn = {1-58113-771-0},
  location = {New York, NY, USA},
  numpages = {2},
  owner = {Mark},
  timestamp = {2013.02.08}
}

@ARTICLE{Zha05,
  author = {Zhang, Xiaoqin and Lesser, Victor R. and Podorozhny, Rodion},
  title = {Multi-Dimensional, MultiStep Negotiation},
  journal = {Autonomous Agents and Multi-Agent Systems},
  year = {2005},
  volume = {10},
  pages = {5-40},
  number = {1},
  doi = {10.1007/s10458-004-5020-3},
  issn = {1387-2532},
  keywords = {cooperative negotiation; distributed search; multi-agent system},
  language = {English},
  publisher = {Kluwer Academic Publishers},
  url = {http://dx.doi.org/10.1007/s10458-004-5020-3}
}

@INPROCEEDINGS{Zhe13,
  author = {Zheng, Ronghuo and Chakraborty, Nilanjan and Dai, Tinglong and Sycara, Katia P.},
  title = {Multiagent negotiation on multiple issues with incomplete information},
  booktitle = {Proceedings of the 2013 international conference on Autonomous agents and multi-agent systems},
  year = {2013},
  pages = {1279--1280},
  organization = {International Foundation for Autonomous Agents and Multiagent Systems}
}

@ARTICLE{Zlo91,
  author = {Zlotkin, Gilad and Rosenschein, Jeffrey S.},
  title = {Cooperation and conflict resolution via negotiation among autonomous agents in noncooperative domains},
  journal = {IEEE Transactions on Systems, Man and Cybernetics},
  year = {1991},
  volume = {21},
  pages = {1317-1324},
  number = {6},
  abstract = {The authors present a theoretical negotiation model for rational agents
        in general noncooperative domains. Necessary and sufficient conditions
        for cooperation are outlined. By redefining the concept of utility,
        it is possible to enlarge the number of situations that have a cooperative
        solution. An approach is offered for conflict resolution, and it
        is shown that even in a conflict situation, partial cooperative steps
        can be taken by interacting agents. A unified negotiation protocol
        is developed that can be used in all cases. It is shown that in certain
        borderline cooperative situations, a partial cooperative agreement
        might be preferred by all agents, even though there exists a rational
        agreement that would achieve all their goals. A deal hierarchy is
        presented that captures the partial order among various kinds of
        deals between agents. The multiplan deal, which involves negotiating
        over a pair of joint plans simultaneously, allows cooperative agreement
        and conflict resolution in both fixed goal and flexible goal domains},
  doi = {10.1109/21.135678},
  issn = {0018-9472},
  keywords = {artificial intelligence;artificial intelligence;autonomous agents;conflict
        resolution;cooperation;deal hierarchy;negotiation;noncooperative
        domains;partial cooperative agreement;rational agents;utility;Absorption;Artificial
        intelligence;Autonomous agents;Computer science;Councils;Helium;Problem-solving;Protocols;Resource
        management;Sufficient conditions}
}

@INPROCEEDINGS{Zuc13,
  author = {Zuckerman, Inon and Segal-Halevi, Erel and Kraus, Sarit and Rosenfeld, Avi},
  title = {Towards Automated Negotiation Agents that use Chat Interface},
  booktitle = {The Sixth International Workshop on Agent-based Complex Automated Negotiations (ACAN)},
  year = {2013},
  month = {May},
  abstract = {To date, a variety of automated negotiation agents have been created.
        While each of these agents has been shown to be effective in negotiating
        with people in speci?c environments, they lack natural language processing
        (NLP) methods required to enable real-world types of interactions.
        In this paper we study how existing agents must be modi?ed to address
        this limitation. After performing an extensive study of agents' negotiation
        with human subjects, we found that simply modifying existing agents
        to include an NLP module is insuf?cient to create these agents. Instead
        the agents' strategies must be modi?ed to address partial agreements
        and issue-by-issue interactions.},
  citeulike-article-id = {12249562},
  day = {6},
  keywords = {negotiative-dialog},
  posted-at = {2013-04-08 11:38:27},
  priority = {0}
}

@BOOK{Aumann92,
  title = {Handbook of Game Theory with Economic Applications},
  publisher = {Elsevier},
  year = {1992},
  editor = {Aumann, Robert J. and Hart, S.},
  volume = {1},
  edition = {1st},
  keywords = {Game theory; economic applications},
  url = {http://EconPapers.repec.org/RePEc:eee:gamhes:1}
}

@PROCEEDINGS{DBLP:conf/ieaaie/2011-2,
  title = {Modern Approaches in Applied Intelligence - 24th International Conference
        on Industrial Engineering and Other Applications of Applied Intelligent
        Systems, IEA/AIE 2011, Syracuse, NY, USA, June 28 - July 1, 2011,
        Proceedings, Part II},
  year = {2011},
  editor = {Kishan G. Mehrotra and Chilukuri K. Mohan and Jae C. Oh and Pramod
        K. Varshney and Moonis Ali},
  volume = {6704},
  series = {Lecture Notes in Computer Science},
  publisher = {Springer},
  bibsource = {DBLP, http://dblp.uni-trier.de},
  booktitle = {IEA/AIE (2)},
  ee = {http://dx.doi.org/10.1007/978-3-642-21827-9},
  isbn = {978-3-642-21826-2}
}

@article{SwitchingCostsAndGittins,
     title = {Switching Costs and the Gittins Index},
     author = {Banks, Jeffrey S. and Sundaram, Rangarajan K.},
     journal = {Econometrica},
     volume = {62},
     number = {3},
     pages = {687-694},
     url = {http://www.jstor.org/stable/2951664},
     ISSN = {00129682},
     language = {English},
     year = {1994},
     publisher = {The Econometric Society},
}

@techreport{GeneralPandoraRule,
  title={A more general pandora rule},
  author={Olszewski, Wojciech and Weber, Richard},
  year={2012},
  institution={Mimeo}
}

@INPROCEEDINGS{EvaluatingPeerDesignedAgentsInMechanismsEvaluation,
author={Elmalech, A. and Sarne, D.},
booktitle={2012 IEEE/WIC/ACM International Conferences on Web Intelligence and Intelligent Agent Technology (WI-IAT)},
title={Evaluating the Applicability of Peer-Designed Agents in Mechanisms Evaluation},
year={2012},
month={Dec},
volume={2},
pages={374-381},
abstract={In this paper we empirically investigate the feasibility of using peer-designed agents (PDAs) instead of people for the purpose of mechanism evaluation. This latter approach has been increasingly advocated in agent research in recent years, mainly due to its many benefits in terms of time and cost. Our experiments compare the behavior of 31 PDAs and 150 people in a legacy eCommerce-based price-exploration setting, using different price-setting mechanisms and different performance measures. The results show a varying level of similarity between the aggregate behavior obtained when using people and when using PDAs -- in some settings similar results were obtained, in others the use of PDAs rather than people yields substantial differences. This suggests that the ability to generalize results from one successful implementation of PDA-based systems to another, regarding the use of PDAs as a substitute to people in systems evaluation, is quite limited. The decision to prefer PDAs for mechanism evaluation is therefore setting dependent and the applicability of the approach must be re-evaluated whenever switching to a new setting or using a different measure. Furthermore, we show that even in settings where the aggregate behavior is found to be similar, the individual strategies used by agents in each group highly vary.},
keywords={electronic commerce;multi-agent systems;PDA-based system;legacy eCommerce;mechanism evaluation;peer-designed agent;price-exploration setting;PDA;system evaluation},
doi={10.1109/WI-IAT.2012.199},
}

@inproceedings{UtilityElicitationAsAClassificationProblem,
 author = {Chajewska, Urszula and Getoor, Lise and Norman, Joseph and Shahar, Yuval},
 title = {Utility Elicitation As a Classification Problem},
 booktitle = {Proceedings of the Fourteenth Conference on Uncertainty in Artificial Intelligence},
 series = {UAI'98},
 year = {1998},
 isbn = {1-55860-555-X},
 location = {Madison, Wisconsin},
 pages = {79--88},
 numpages = {10},
 url = {http://dl.acm.org/citation.cfm?id=2074094.2074104},
 acmid = {2074104},
 publisher = {Morgan Kaufmann Publishers Inc.},
 address = {San Francisco, CA, USA},
}

@inproceedings{DeterminingInternetUsersValuesForPrivateInformation,
  author    = {Scott Buffett and Nathan Scott and Bruce Spencer and Michael Richter and Michael W. Fleming},
  title     = {Determining Internet Users' Values for Private Information},
  booktitle = {Second Annual Conference on Privacy, Security and Trust, October 13-15, 2004, Wu Centre, University of New Brunswick, Fredericton, New Brunswick, Canada, Proceedings},
  year      = {2004},
  pages     = {79--88},
  url       = {http://dev.hil.unb.ca/Texts/PST/pdf/buffett.pdf},
  timestamp = {Thu, 23 Oct 2014 13:03:13 +0200},
  biburl    = {http://dblp.uni-trier.de/rec/bib/conf/pst/BuffettSSRF04},
  bibsource = {dblp computer science bibliography, http://dblp.org}
}

@inproceedings{APOMDPFormulationOfPreferenceElicitationProblems,
 author = {Boutilier, Craig},
 title = {A {POMDP} Formulation of Preference Elicitation Problems},
 booktitle = {Eighteenth National Conference on Artificial Intelligence},
 year = {2002},
 isbn = {0-262-51129-0},
 location = {Edmonton, Alberta, Canada},
 pages = {239--246},
 numpages = {8},
 url = {http://dl.acm.org/citation.cfm?id=777092.777132},
 acmid = {777132},
 publisher = {American Association for Artificial Intelligence},
 address = {Menlo Park, CA, USA},
}

@BOOK{PrinciplesOfAutomatedNegotiation,
  title = {Principles of Automated Negotiation},
  publisher = {Cambridge University Press},
  isbn = {9781107002548},
  year = {2014},
  author = {Shaheen Fatima and Sarit Kraus and Michael J. Wooldridge},
  pages = {289}
}

@inproceedings{ADecisionProcedureForAutonomousAgentsToReasonAboutInteractionWithHumans,
  title={A decision procedure for autonomous agents to reason about interaction with humans},
  author={Fleming, Michael W. and Cohen, Robin},
  booktitle={Proceedings of the AAAI 2004 Spring Symposium on Interaction between Humans and Autonomous Systems over Extended Operation},
  pages={81--86},
  year={2004}
}

@article{AuctionDesignWithCostlyPreferenceElicitation,
year={2005},
issn={1012-2443},
journal={Annals of Mathematics and Artificial Intelligence},
volume={44},
number={3},
doi={10.1007/s10472-005-4692-y},
title={Auction design with costly preference elicitation},
url={http://dx.doi.org/10.1007/s10472-005-4692-y},
publisher={Kluwer Academic Publishers},
keywords={computational mechanism design; incremental revelation principle; meta-deliberation; proxy agents; preference elicitation},
author={Parkes, David C.},
pages={269-302},
language={English}
}

@INPROCEEDINGS{MinimalPreferenceElicitationInCombinatorialAuctions,
    author = {Wolfram Conen and Tuomas Sandholm},
    title = {Minimal Preference Elicitation in Combinatorial Auctions},
    booktitle = {In Proceedings of the Seventeenth International Joint Conference on Artificial Intelligence, Workshop on Economic Agents, Models, and Mechanisms},
    year = {2001},
    pages = {71--80}
}

@INPROCEEDINGS{MakingRationalDecisionsUsingAdaptiveUtilityElicitation,
    author = {Urszula Chajewska and Daphne Koller and Ronald Parr},
    title = {Making Rational Decisions using Adaptive Utility Elicitation},
    booktitle = {In Proceedings of the Seventeenth National Conference on Artificial Intelligence},
    year = {2000},
    pages = {363--369}
}

@INPROCEEDINGS{Gir04,
author={Girard, A.R. and Howell, A.S. and Hedrick, J.K.},
booktitle={43rd IEEE Conference on Decision and Control, 2004. CDC.},
title={Border patrol and surveillance missions using multiple unmanned air vehicles},
year={2004},
month={Dec},
volume={1},
pages={620-625},
abstract={In this paper, we propose hierarchical control architecture for a system that does border or perimeter patrol using unmanned air vehicles (AUV). By control architecture we mean a specific way of organizing the motion control and navigation functions performed by the UAV. It is convenient to organize the functions into hierarchical layers. This way, a complex design problem is partitioned into a number of more manageable subproblems that are addressed in separate layers. This paper discusses vehicle control requirements and maps them onto layered control architecture. The formalization of the hierarchy is accomplished in terms of the specific functions accomplished by each layer and of the interfaces between layers. The implementation of the layers is discussed and illustrative examples are provided.},
keywords={aircraft control;motion control;remotely operated vehicles;surveillance;border patrol;complex design problem;hierarchical control architecture;layered control architecture;motion control;multiple unmanned air vehicles;surveillance mission;Control systems;Intelligent sensors;Mechanical engineering;Motion control;Navigation;Organizing;Supervisory control;Surveillance;Trajectory;Unmanned aerial vehicles},
doi={10.1109/CDC.2004.1428713},
ISSN={0191-2216}
}

@incollection{MechanismDesignForTaskProcurementWithFlexibleQualityOfService,
year={2009},
isbn={978-3-642-10738-2},
booktitle={Service-Oriented Computing: Agents, Semantics, and Engineering},
volume={5907},
series={Lecture Notes in Computer Science},
editor={Kowalczyk, Ryszard and Vo, QuocBao and Maamar, Zakaria and Huhns, Michael},
doi={10.1007/978-3-642-10739-9_2},
title={Mechanism Design for Task Procurement with Flexible Quality of Service},
url={http://dx.doi.org/10.1007/978-3-642-10739-9_2},
publisher={Springer Berlin Heidelberg},
author={Gerding, Enrico H. and Larson, Kate and Rogers, Alex and Jennings, Nicholas R.},
pages={12-23},
language={English}
}

@article{SimultaneousSearch,
author = {Chade, Hector and Smith, Lones},
title = {Simultaneous Search},
journal = {Econometrica},
volume = {74},
number = {5},
publisher = {Blackwell Publishing Ltd},
issn = {1468-0262},
url = {http://dx.doi.org/10.1111/j.1468-0262.2006.00705.x},
doi = {10.1111/j.1468-0262.2006.00705.x},
pages = {1293--1307},
keywords = {Search, portfolio choice, submodular, greedy algorithm},
year = {2006},
}

@article{OptimalSearchInNegotiation,
     title = {Optimal Search in Negotiation Analysis},
     author = {Lax, David A.},
     journal = {The Journal of Conflict Resolution},
     volume = {29},
     number = {3},
     pages = {456-472},
     url = {http://www.jstor.org/stable/173945},
     ISSN = {00220027},
     abstract = {A negotiator's reservation price or "bottom line" depends directly on the value of the no-agreement alternative to a proposed negotiated agreement. Often, one's no-agreement alternatives are uncertain and finding them requires a costly search, as in the case of a seller who must expend effort, time, and money in finding potential buyers. The value of the search should determine the seller's bottom-line or reservation price in dealings with a prospective buyer. Optimal search and stopping theory suggest useful procedures and heuristics for evaluating one's reservation price in negotiation and for searching among alternatives.},
     language = {English},
     year = {1985},
     publisher = {Sage Publications, Inc.},
    }
        
@inproceedings{AspirationAdaptationTheoryToImproveLearning,
 author = {Rosenfeld, Avi and Kraus, Sarit},
 title = {Using Aspiration Adaptation Theory to Improve Learning},
 booktitle = {The 10th International Conference on Autonomous Agents and Multiagent Systems},
 volume = {1},
 series = {AAMAS '11},
 year = {2011},
 isbn = {0-9826571-5-3, 978-0-9826571-5-7},
 location = {Taipei, Taiwan},
 pages = {423--430},
 numpages = {8},
 url = {http://dl.acm.org/citation.cfm?id=2030470.2030533},
 acmid = {2030533},
 publisher = {International Foundation for Autonomous Agents and Multiagent Systems},
 address = {Richland, SC},
 keywords = {agent learning, bounded rationality, cognitive models},
}

@inproceedings{CostlyValuationComputationInAuctions,
 author = {Larson, Kate and Sandholm, Tuomas},
 title = {Costly Valuation Computation in Auctions},
 booktitle = {Proceedings of the 8th Conference on Theoretical Aspects of Rationality and Knowledge},
 series = {TARK '01},
 year = {2001},
 isbn = {1-55860-791-9},
 location = {Siena, Italy},
 pages = {169--182},
 numpages = {14},
 url = {http://dl.acm.org/citation.cfm?id=1028128.1028148},
 acmid = {1028148},
 publisher = {Morgan Kaufmann Publishers Inc.},
 address = {San Francisco, CA, USA},
}

@article{Ji14,
        year={2014},
        issn={0924-669X},
        journal={Applied Intelligence},
        volume={40},
        number={4},
        doi={10.1007/s10489-013-0497-6},
        title={A one-shot bargaining strategy for dealing with multifarious opponents},
        url={http://dx.doi.org/10.1007/s10489-013-0497-6},
        publisher={Springer US},
        keywords={Bargain; Strategy; Heuristic method; Prediction; Experimental analysis},
        author={Ji, Shu-juan and Zhang, Chun-jin and Sim, Kwang-Mong and Leung, {Ho-fung}},
        pages={557-574},
        language={English}
}

@inproceedings{Yan12,
         author = {Yang, Yinping},
         title = {A Review of Strategy Design and Evaluation of Software Negotiation Agents},
         booktitle = {Proceedings of the 14th Annual International Conference on Electronic Commerce},
         series = {ICEC '12},
         year = {2012},
         isbn = {978-1-4503-1197-7},
         location = {Singapore, Singapore},
         pages = {155--156},
         numpages = {2},
         url = {http://doi.acm.org/10.1145/2346536.2346565},
         doi = {10.1145/2346536.2346565},
         acmid = {2346565},
         publisher = {ACM},
         address = {New York, NY, USA},
         keywords = {automated negotiation, negotiation agent, negotiation strategy},
}

@inproceedings{AnExperimentalComparisonOfClickPosition-biasModels,
 author = {Craswell, Nick and Zoeter, Onno and Taylor, Michael and Ramsey, Bill},
 title = {An Experimental Comparison of Click Position-bias Models},
 booktitle = {Proceedings of the 2008 International Conference on Web Search and Data Mining},
 series = {WSDM '08},
 year = {2008},
 isbn = {978-1-59593-927-2},
 location = {Palo Alto, California, USA},
 pages = {87--94},
 numpages = {8},
 url = {http://doi.acm.org/10.1145/1341531.1341545},
 doi = {10.1145/1341531.1341545},
 acmid = {1341545},
 publisher = {ACM},
 address = {New York, NY, USA},
 keywords = {click data, user behavior, web search models},
}

@inproceedings{ACascadeModelForExternalitiesInSponsoredSearch,
 author = {Kempe, David and Mahdian, Mohammad},
 title = {A Cascade Model for Externalities in Sponsored Search},
 booktitle = {Proceedings of the 4th International Workshop on Internet and Network Economics},
 series = {WINE '08},
 year = {2008},
 isbn = {978-3-540-92184-4},
 location = {Shanghai, China},
 pages = {585--596},
 numpages = {12},
 url = {http://dx.doi.org/10.1007/978-3-540-92185-1_65},
 doi = {10.1007/978-3-540-92185-1_65},
 acmid = {1505022},
 publisher = {Springer-Verlag},
 address = {Berlin, Heidelberg},
}

@Article{AGenericFrameworkForAutomatedMulti-attributeNegotiation,
  author    = {Lai, Guoming and Sycara, Katia P.},
  title     = {A Generic Framework for Automated Multi-attribute Negotiation},
  journal   = {Group Decision and Negotiation},
  year      = {2009},
  volume    = {18},
  number    = {2},
  pages     = {169-187},
  doi       = {10.1007/s10726-008-9119-9},
  issn      = {0926-2644},
  keywords  = {Automated multi-attribute negotiation; Incomplete information; Pareto optimality; Mediating; Win-win},
  language  = {English},
  publisher = {Springer Netherlands},
  url       = {http://dx.doi.org/10.1007/s10726-008-9119-9},
}

@Article{Zha15,
  author   = {Jihang Zhang and Fenghui Ren and Minjie Zhang},
  title    = {Bayesian-based preference prediction in bilateral multi-issue negotiation between intelligent agents},
  journal  = {Knowledge-Based Systems},
  year     = {2015},
  abstract = {Agent negotiation is a form of decision making where two or more agents jointly search for a mutually agreed solution to a certain problem. In multi-issue negotiation, with information available about the agents' preferences, a negotiation may result in a mutually beneficial agreement. In a competitive negotiation environment, however, self-interested agents may not be willing to reveal their preferences, and this can increase the difficulty of negotiating a mutually beneficial agreement. In order to solve this problem, this paper proposes a Bayesian-based approach which can help an agent to predict its opponent's preference in bilateral multi-issue negotiation. The proposed approach employs Bayesian theory to analyse the opponent's historical offers and to approximately predict the opponent's preference over negotiation issues. A counter-offer proposition algorithm is also integrated into the prediction approach to help agents to propose mutually beneficial offers based on the prediction results. Experimental results indicate good performance of the proposed approach in terms of utility gain and negotiation efficiency.},
  doi      = {http://dx.doi.org/10.1016/j.knosys.2015.04.006},
  issn     = {0950-7051},
  keywords = {Opponent modelling},
  url      = {http://www.sciencedirect.com/science/article/pii/S0950705115001446},
}

@article{DOPPONENT,
        author = {Farhad Zafari and Faria Nassiri-Mofakham and Ali Zeinal Hamadani},
        title = {DOPPONENT: A Socially Efficient Preference Model of Opponent in Bilateral Multi Issue Negotiations},
        journal = {Journal of Computing and Security},
        volume = {1},
        number = {4},
        year = {2015},
        abstract = { During the last decades, opponent modeling techniques, utilized to improve the negotiation outcome, have sparked interest in the negotiation research community. In this study, we first investigate the applicability of nearest neighbor method with different distance functions in modeling the opponent's preferences. Then, we introduce a new distance-based model to extract the opponent's preferences in a bilateral multi issue negotiation session. We devise an experiment to evaluate the efficiency of our proposed model in a real negotiation setting in terms of a number of performance measures.},
        issn = {2383-0417},     
        url = {http://www.jcomsec.org/index.php/JCS/article/view/130}
}

@article{ABINES,
title = "An efficient and robust negotiating strategy in bilateral negotiations over multiple items",
journal = "Engineering Applications of Artificial Intelligence",
volume = "34",
pages = "45 - 57",
year = "2014",
issn = "0952-1976",
doi = "http://dx.doi.org/10.1016/j.engappai.2014.05.008",
url = "http://www.sciencedirect.com/science/article/pii/S0952197614001067",
author = {Jianye Hao and Songzheng Song and {Ho-fung} Leung and Zhong Ming},
keywords = "Bilateral negotiation",
abstract = "Abstract Multi-item negotiations surround our daily life and usually involve two parties that share common or conflicting interests. Effective automated negotiation techniques should enable the agents to adaptively adjust their behaviors depending on the characteristics of their negotiating partners and negotiation scenarios. This is complicated by the fact that the negotiation agents are usually unwilling to reveal their information (strategies and preferences) to avoid being exploited during negotiation. In this paper, we propose an adaptive negotiation strategy, called ABiNeS, which can make effective negotiations against different types of negotiating partners. The \{ABiNeS\} strategy employs the non-exploitation point to adaptively adjust the appropriate time to stop exploiting the negotiating partner and also predicts the optimal offer for the negotiating partner based on the reinforcement-learning based approach. Simulation results show that the \{ABiNeS\} strategy can perform more efficient exploitations against different types of negotiating partners, and thus achieve higher overall payoffs compared with the state-of-the-art strategies under negotiation tournaments. We also provide a detailed analysis of why the \{ABiNeS\} strategy can negotiate more efficiently compared with other existing state-of-the-art negotiation strategies focusing on two major components. Lastly, we propose adopting the single-agent best deviation principle to analyze the robustness of different negotiation strategies based on model checking techniques. Through our analysis, the \{ABiNeS\} strategy is shown to be very robust against other state-of-the-art strategies under different negotiation contexts. "
}

@article{SimultaneousSelection,
  title={Simultaneous Selection},
  author={Olszewski, Wojciech and Vohra, Rakesh},
  year={2014},
  url = {http://faculty.wcas.northwestern.edu/~wol737/Selc.pdf}
}

@inproceedings{Zlo89,
 author = {Zlotkin, Gilad and Rosenschein, Jeffrey S.},
 title = {Negotiation and Task Sharing Among Autonomous Agents in Cooperative Domains},
 booktitle = {Proceedings of the 11th International Joint Conference on Artificial Intelligence},
 volume = {2},
 series = {IJCAI'89},
 year = {1989},
 location = {Detroit, Michigan},
 pages = {912--917},
 numpages = {6},
 url = {http://dl.acm.org/citation.cfm?id=1623891.1623901},
 acmid = {1623901},
 publisher = {Morgan Kaufmann Publishers Inc.},
 address = {San Francisco, CA, USA},
} 


@article{IssuesInMultiagentResourceAllocation,
volume = {30},
title = {Issues in Multiagent Resource Allocation},
author = {Yann Chevaleyre and Paul E. Dunne and Ulle Endriss and J\'er\^ome Lang and Michel Lema\^itre and Nicolas Maudet and Julian Padget and Steve Phelps and Juan A. Rodr\'iguez-Aguilar and Paulo Sousa},
year = {2006},
pages = {3---31},
journal = {Informatica},
url = {http://opus.bath.ac.uk/5362/}
}

@article{PreferencesInAIAnOverview,
 author = {Domshlak, Carmel and H\"{u}llermeier, Eyke and Kaci, Souhila and Prade, Henri},
 title = {Preferences in {AI}: An Overview},
 journal = {Artificial Intelligence},
 issue_date = {May, 2011},
 volume = {175},
 number = {7-8},
 month = {May},
 year = {2011},
 issn = {0004-3702},
 pages = {1037--1052},
 numpages = {16},
 url = {http://dx.doi.org/10.1016/j.artint.2011.03.004},
 doi = {10.1016/j.artint.2011.03.004},
 acmid = {1969961},
 publisher = {Elsevier Science Publishers Ltd.},
 address = {Essex, UK},
 keywords = {Aggregation functions, Graphical representation, Logical representation, Preference, Preference learning, Preference queries},
} 

@InProceedings{Che04kadditive,
  author    = {Chevaleyre, Yann and Endriss, Ulle and Estivie, Sylvia and Maudet, Nicolas},
  title     = {Multiagent resource allocation with k-additive utility functions},
  booktitle = {Proceedings of the DIMACS-LAMSADE Workshop on Computer Science and Decision Theory},
  year      = {2004},
  pages     = {83-100},
}

@inproceedings{Had14,
  title={Addressing complexity in multi-issue negotiation via utility hypergraphs},
  author={Hadfi, Rafik and Ito, Takayuki},
  booktitle={Proceedings of the Twenty-Eighth AAAI Conference on Artificial Intelligence},
  year={2014}
}

@book{ACANProceedings2011,
  title={New trends in agent-based complex automated negotiations},
  author={Ito, Takayuki and Zhang, Minjie and Robu, Valentin and Fatima, Shaheen and Matsuo, Tokuro},
  volume={383},
  year={2011},
  publisher={Springer Science \& Business Media}
}

@book{ACANProceedings2014,
  title={Novel Insights in Agent-based Complex Automated Negotiation},
  author={Marsa-Maestre, Ivan and Lopez-Carmona, Miguel A. and Ito, Takayuki and Zhang, Minjie and Bai, Quan and Fujita, Katsuhide},
  volume={535},
  year={2014},
  publisher={Springer}
}

@article{BiddingLanguages,
  title={Bidding languages},
  author={Nisan, Noam},
  journal={Combinatorial auctions. Cambridge: MIT},
  year={2006}
}

@phdthesis{DaveThesis,
author="Dave de Jonge",
title="Negotiations over Large Agreement Spaces",
school="Universitat Aut\`{o}noma de Barcelona",
year="2015",
}

@inproceedings{ExpectedExpectedUtility,
 author = {Boutilier, Craig},
 title = {On the Foundations of Expected Expected Utility},
 booktitle = {Proceedings of the 18th International Joint Conference on Artificial Intelligence},
 series = {IJCAI'03},
 year = {2003},
 location = {Acapulco, Mexico},
 pages = {285--290},
 numpages = {6},
 url = {http://dl.acm.org/citation.cfm?id=1630659.1630701},
 acmid = {1630701},
 publisher = {Morgan Kaufmann Publishers Inc.},
 address = {San Francisco, CA, USA},
} 

@InProceedings{An10,
  author    = {An, Bo and Lesser, Victor and Irwin, David and Zink, Michael},
  title     = {Automated Negotiation with Decommitment for Dynamic Resource Allocation in Cloud Computing},
  booktitle = {Proceedings of the 9th International Conference on Autonomous Agents and Multiagent Systems: Volume 1 - Volume 1},
  year      = {2010},
  series    = {AAMAS '10},
  pages     = {981--988},
  address   = {Richland, SC},
  publisher = {International Foundation for Autonomous Agents and Multiagent Systems},
  acmid     = {1838338},
  isbn      = {978-0-9826571-1-9},
  keywords  = {automated negotiation, cloud computing, negotiation strategy},
  location  = {Toronto, Canada},
  numpages  = {8},
  url       = {http://dl.acm.org/citation.cfm?id=1838206.1838338},
}

@Article{PowerTAC,
  author   = {Wolfgang Ketter and John Collins and Prashant Reddy},
  title    = {Power TAC: A competitive economic simulation of the smart grid},
  journal  = {Energy Economics},
  year     = {2013},
  volume   = {39},
  pages    = {262 - 270},
  abstract = {Abstract Sustainable energy systems of the future will need more than efficient, clean, low-cost, renewable energy sources; they will also need efficient price signals that motivate sustainable energy consumption as well as a better real-time alignment of energy demand and supply. The Power Trading Agent Competition (Power TAC) is a rich competitive simulation of future retail power markets. This simulation will help us to understand the dynamics of customer and retailer decision-making and the robustness of market designs, by stimulating researchers to develop broker agents and benchmark them against each other. This will provide compelling, actionable information for policymakers and industry leaders. We describe the competition scenario in detail, and we demonstrate behaviors that arise from the interaction of customer and broker models. },
  doi      = {http://dx.doi.org/10.1016/j.eneco.2013.04.015},
  issn     = {0140-9883},
  keywords = {Competitive simulation, Smart grid, Trading agents, Energy markets },
  url      = {http://www.sciencedirect.com/science/article/pii/S0140988313000959},
}

@InProceedings{Ram04,
  author    = {Ramchurn, Sarvapali D. and Deitch, Benjamin and Thompson, Mark K. and De Roure, David C. and Jennings, Nicholas R. and Luck, Michael},
  title     = {Minimising intrusiveness in pervasive computing environments using multi-agent negotiation},
  booktitle = {Mobile and Ubiquitous Systems: Networking and Services, 2004. MOBIQUITOUS 2004. The First Annual International Conference on},
  year      = {2004},
  pages     = {364-371},
  month     = {Aug},
  abstract  = {This paper highlights intrusiveness as a key issue in the field of pervasive computing environments and presents a multiagent approach to tackling it. Specifically, we discuss how interruptions can impact on individual and group tasks and how they can be managed by taking into account user and group preferences through negotiation between software agents. The system we develop is implemented on the Jabber platform and is deployed in the context of a meeting room scenario.},
  doi       = {10.1109/MOBIQ.2004.1331743},
  keywords  = {message passing;multi-agent systems;software agents;ubiquitous computing;Jabber platform;group preference;multiagent approach;pervasive computing;software agent;Books;Communications technology;Computer science;Context;Mobile handsets;Personal digital assistants;Pervasive computing;Portable computers;Power system interconnection;Software agents},
}

@InProceedings{Zhou2014automatic,
  author       = {Zhou, Shuang and Chen, Siqi and Smirnov, Evgueni and Weiss, Gerhard and Tuyls, Karl},
  title        = {Automatic Knowledge Transfer for Agent-based Bilateral Negotiation Tasks},
  booktitle    = {International Workshop on Agent-based Complex Automated Negotiations},
  year         = {2014},
  organization = {Citeseer},
}

@InProceedings{Fujita2014compromising,
  author    = {Fujita, Katsuhide},
  title     = {Compromising strategy based on conflict mode for multi-times bilateral closed negotiations},
  booktitle = {Proceedings of the Seventh International Workshop on Agent-based Complex Automated Negotiations (ACAN 2014)},
  year      = {2014},
}

@InBook{Fujita2014compromisingPRIMA,
  pages     = {439--454},
  title     = {Compromising Adjustment Based on Conflict Mode for Multi-times Bilateral Closed Nonlinear Negotiations},
  publisher = {Springer International Publishing},
  year      = {2014},
  author    = {Fujita, Katsuhide},
  editor    = {Dam, Hoa Khanh and Pitt, Jeremy and Xu, Yang and Governatori, Guido and Ito, Takayuki},
  address   = {Cham},
  booktitle = {PRIMA 2014: Principles and Practice of Multi-Agent Systems: 17th International Conference, Gold Coast, QLD Australia, December 1-5, 2014. Proceedings},
  doi       = {10.1007/978-3-319-13191-7_35},
  isbn      = {978-3-319-13191-7},
  url       = {http://dx.doi.org/10.1007/978-3-319-13191-7_35},
}

@InProceedings{CloudComputingNegotiation,
  author    = {Alsrheed, Faisal and El Rhalibi, Abdennour and Randles, Martin and Merabti, Madjid},
  title     = {Intelligent agents for automated cloud computing negotiation},
  booktitle = {2014 International Conference on Multimedia Computing and Systems (ICMCS)},
  year      = {2014},
  pages     = {1169-1174},
  month     = {April},
  abstract  = {Presently, cloud providers offer off-the-shelf Service Level Agreements (SLA), on a take it or leave it basis. This paper, alternatively, proposes customized SLAs. An automated negotiation is needed to establish customized SLAs between service providers and consumers with no previous knowledge of each other. Traditional negotiations between humans are often fraught with difficulty. Thus, in this work, the use of intelligent agents to represent cloud providers and consumers is advocated. Rubinstein's Alternating Offers Protocol offers a suitable technical solution for this challenging problem. The purpose of this paper is to apply the state-of-the-art in negotiation automated algorithms/agents within a described Cloud Computing SLA framework, and to evaluate the most appropriate negotiation approach based on many criteria.},
  doi       = {10.1109/ICMCS.2014.6911305},
  keywords  = {cloud computing;contracts;multi-agent systems;Rubinstein alternating offers protocol;SLA;automated cloud computing negotiation;cloud computing SLA framework;intelligent agents;service consumers;service level agreements;service providers;take-it-or-leave-it SLA;Bars;Bayes methods;Cloud computing;Educational institutions;Intelligent agents;Monitoring;Protocols;Automated Negotiation;Cloud computing;Service Level Agreements (SLA) management;intelligent agents},
}

@InProceedings{CloudComputingNegotiation2,
  author    = {Alsrheed, Faisal and El Rhalibi, Abdennour and Randles, Martin and Merabti, Madjid},
  title     = {Rubinstein's alternating offers protocol for automated cloud computing negotiation},
  booktitle = {Proceedings of the 14th Annual PG Symposium on the Convergence of Telecommunications, Networking, and Broadcasting},
  year      = {2013},
}

@InProceedings{Che13boltzmann,
  author    = {Chen, Siqi and Ammar, Haitham Bou and Tuyls, Karl and Weiss, Gerhard},
  title     = {Conditional Restricted Boltzmann Machines for Negotiations in Highly Competitive and Complex Domains},
  booktitle = {Proceedings of the Twenty-Third International Joint Conference on Artificial Intelligence},
  year      = {2013},
  series    = {IJCAI '13},
  pages     = {69--75},
  publisher = {AAAI Press},
  acmid     = {2540141},
  isbn      = {978-1-57735-633-2},
  location  = {Beijing, China},
  numpages  = {7},
  url       = {http://dl.acm.org/citation.cfm?id=2540128.2540141},
}

@InProceedings{Fuj14,
  author    = {Katsuhide Fujita},
  title     = {Efficient Strategy Adaptation for Complex Multi-times Bilateral Negotiations},
  booktitle = {2014 IEEE 7th International Conference on Service-Oriented Computing and Applications},
  year      = {2014},
  pages     = {207-214},
  month     = {Nov},
  abstract  = {Bilateral multi-issue closed negotiation is an important class for real-life negotiations. Usually, negotiation problems have constraints such as a complex and unknown opponent's utility in real time, or time discounting. In the class of negotiation with some constraints, the effective automated negotiation agents can adjust their behavior depending on the characteristics of their opponents and negotiation scenarios. Recently, the attention of this study has focused on the interleaving learning with negotiation strategies from the past negotiation sessions. By analyzing the past negotiation sessions, agents can estimate the opponent's utility function based on exchanging bids. In this paper, we propose an automated agent that estimates the opponent's strategies based on the past negotiation sessions. Our agent tries to compromise to the estimated maximum utility of the opponent by the end of the negotiation. In addition, our agent can adjust the speed of compromise by judging the opponent's Thomas-Kilmann Conflict Mode and search for the pareto frontier using past negotiation sessions. In the experiments, we demonstrate that the proposed agent has better outcomes and greater search technique for the pareto frontier than existing agents in the linear and nonlinear utility functions.},
  doi       = {10.1109/SOCA.2014.13},
  issn      = {2163-2871},
  keywords  = {Pareto analysis;negotiation support systems;software agents;utility theory;Pareto frontier;Thomas-Kilmann conflict mode;automated agent;complex multitimes bilateral negotiations;linear utility functions;maximum utility estimation;nonlinear utility functions;opponents strategy estimation;search technique;Adaptation models;Autoregressive processes;Contracts;Instruments;Pareto optimization;Proposals;Protocols;Agreement Technology;Multi-agent System;Multi-issue Negotiation},
}

@InBook{ABINESrationality,
  pages     = {115--142},
  title     = {Individual Rationality in Competitive Multiagent Systems},
  publisher = {Springer Berlin Heidelberg},
  year      = {2016},
  author    = {Hao, Jianye and Leung, Ho-fung},
  address   = {Berlin, Heidelberg},
  booktitle = {Interactions in Multiagent Systems: Fairness, Social Optimality and Individual Rationality},
  doi       = {10.1007/978-3-662-49470-7_5},
  isbn      = {978-3-662-49470-7},
  url       = {http://dx.doi.org/10.1007/978-3-662-49470-7_5},
}

@Article{POPPONENT,
  author   = {Farhad Zafari and Faria Nassiri-Mofakham},
  title    = {POPPONENT: Highly accurate, individually and socially efficient opponent preference model in bilateral multi issue negotiations},
  journal  = {Artificial Intelligence},
  year     = {2016},
  volume   = {237},
  pages    = {59 - 91},
  abstract = {Abstract In automated bilateral multi issue negotiations, two intelligent automated agents negotiate on behalf of their owners regarding many issues in order to reach an agreement. Modeling the opponent can excessively boost the performance of the agents and increase the quality of the negotiation outcome. State of the art models accomplish this by considering some assumptions about the opponent which restricts the applicability of the models in real scenarios. In this study, a less restricted technique where perceptron units (POPPONENT) are applied in modeling the preferences of the opponent is proposed. This model adopts the Multi Bipartite version of the Standard Gradient Descent search algorithm (MBGD) to find the best hypothesis, which is the best preference profile. In order to evaluate the accuracy and performance of this proposed opponent model, it is compared with the state of the art models available in the Genius repository. This results in the devised setting which approves the higher accuracy of \{POPPONENT\} compared to the most accurate state of the art model. Evaluating the model in the real world negotiation scenarios in the Genius framework also confirms its high accuracy in relation to the state of the art models in estimating the utility of offers. The findings here indicate that this proposed model is individually and socially efficient. This proposed \{MBGD\} method could also be adopted in other practical areas of Artificial Intelligence. },
  doi      = {http://dx.doi.org/10.1016/j.artint.2016.04.001},
  issn     = {0004-3702},
  keywords = {Bilateral multi issue negotiation, Opponent modeling, Bidding strategy, Acceptance strategy, Perceptron, Multi bipartite gradient descent },
  url      = {http://www.sciencedirect.com/science/article/pii/S0004370216300364},
}

@InProceedings{Fuj15TKI,
  author    = {Katsuhide Fujita},
  title     = {{TKI} Adaptation Strategy for Complex Multi-times Bilateral Negotiations},
  booktitle = {2015 IEEE 8th International Conference on Service-Oriented Computing and Applications (SOCA)},
  year      = {2015},
  pages     = {232-236},
  month     = {Oct},
  abstract  = {Bilateral multi-issue closed negotiation is an important class for real-life negotiations. Usually, negotiation problems have constraints such as a complex and unknown opponent's utility in real time, or time discounting. Recently, the attention of this study has focused on the nonlinear utility functions. In nonlinear utility functions, most of the negotiation strategies for linear utility functions can't adopt to the scenarios of nonlinear utility functions. In this paper, we propose an automated agent that estimates the opponent's strategies based on the past negotiation sessions. Our agent tries to compromise to the estimated maximum utility of the opponent by the end of the negotiation. In addition, our agent can adjust the speed of compromise by judging the opponent's Thomas-Kilmann Conflict Mode and search for the pare to frontier using past negotiation sessions. In the experiments, we demonstrate that the proposed agent has better outcomes and greater search technique than existing agents.},
  doi       = {10.1109/SOCA.2015.30},
  keywords  = {multi-agent systems;negotiation support systems;TKI adaptation strategy;Thomas-Kilmann conflict mode;automated agent;bilateral multi-issue closed negotiation;linear utility functions;multi-times bilateral negotiation;negotiation strategy;nonlinear utility functions;Contracts;Instruments;Mathematical model;Pareto optimization;Proposals;Protocols;Search methods;Agreement Technology;Multi-agent System;Multi-issue Negotiation},
}

@Article{Lan12elicitating,
  author = {Lang, Fabian and Schryen, Guido and Fink, Andreas},
  title  = {Elicitating, modeling, and processing uncertain human preferences for software agents in electronic negotiations: an empirical study},
  year   = {2012},
}


@inproceedings{Zlo91Inc,
 author = {Zlotkin, Gilad and Rosenschein, Jeffrey S.},
 title = {Incomplete Information and Deception in Multi-agent Negotiation},
 booktitle = {Proceedings of the 12th International Joint Conference on Artificial Intelligence - Volume 1},
 series = {IJCAI'91},
 year = {1991},
 isbn = {1-55860-160-0},
 location = {Sydney, New South Wales, Australia},
 pages = {225--231},
 numpages = {7},
 url = {http://dl.acm.org/citation.cfm?id=1631171.1631205},
 acmid = {1631205},
 publisher = {Morgan Kaufmann Publishers Inc.},
 address = {San Francisco, CA, USA},
}

@inproceedings{Ngu03Inc,
       booktitle = {International Joint Conferences on Artificial Intelligence},
           title = {A heuristic model of concurrent bi-lateral negotiations in incomplete information settings},
          author = {Thuc Duong Nguyen and Nicholas R. Jennings},
            year = {2003},
           pages = {1467--1469},            
        keywords = {negotiation, concurrent, bi-lateral, heuristic},
             url = {http://eprints.soton.ac.uk/257433/},
        abstract = {Bi-lateral negotiations represent an important class of encounter in agent-based systems. To this end, this paper develops and evaluates a heuristic model that enables an agent to participate in multiple, concurrent bi-lateral encounters in competitive situations in which there is information uncertainty and deadlines.}
}

@article{DefaultThenAdjust,
          volume = {64},
          number = {4},
           title = {Acquiring User Strategies and Preferences for Negotiating Agents: A Default Then Adjust Method},
          author = {Luo, Xudong and Jennings, Nicholas R. and Shadbolt, Nigel},
            year = {2006},
           pages = {304--321},
         journal = {International Journal of Human Computer Studies},
        keywords = {Tradeoff Strategy and Preference; Knowledge Aquisition; Preference Aquisition; Automated Negotiaition; Software Agents},
             url = {http://eprints.soton.ac.uk/264474/},
        abstract = {A wide range of algorithms have been developed for various types of negotiating agents. In developing such algorithms the main focus has been on their efficiency and their effectiveness. However, this is only a part of the picture. Typically, agents negotiate on behalf of their owners and for this to be effective the agents must be able to adequately represent their owners? strategies and preferences for negotiation. However, the process by which such knowledge is acquired is typically left unspecified. To address this problem, we undertook a study of how user information about negotiation tradeoff strategies and preferences can be captured. Specifically, we devised a novel default-then-adjust acquisition technique. In this, the system firstly does a structured interview with the user to suggest the attributes that the tradeoff could be made between, then it asks the user to adjust the suggested default tradeoff strategy by improving some attribute to see how much worse the attribute being traded off can be made while still being acceptable, and, finally, it asks the user to adjust the default preference on the tradeoff alternatives. This method is consistent with the principles of standard negotiation theory and to demonstrate its effectiveness we implemented a prototype system and performed an empirical evaluation in an accommodation renting scenario. The result of this evaluation indicates the proposed technique is helpful and efficient in accurately acquiring the users? tradeoff strategies and preferences.}
}

@Article{Del16,
  author      = {Delecroix, Fabien and Morge, Maxime and Nachtergaelle, Thomas and Routier, Jean-Christophe},
  title       = {Multi-party negotiation with preferences rather than utilities},
  journal     = {Multiagent and Grid Systems - An International Journal of Cloud Computing},
  year        = {2016},
  volume      = {12},
  number      = {2},
  pages       = {27},
  doi         = {10.3233/MGS-160248},
  hal_id      = {hal-01327502},
  hal_version = {v1},
  keywords    = {Conflict handling ; Negotiation ; Distributed Problem Solving},
  publisher   = {IOS Press},
  url         = {https://hal.inria.fr/hal-01327502},
}
@Article{Ble99,
  author   = {Barry Blecherman},
  title    = {Adopting automated negotiation},
  journal  = {Technology in Society},
  year     = {1999},
  volume   = {21},
  number   = {2},
  pages    = {167 - 174},
  abstract = {The developing technology of automated negotiation is examined and issues relating to the adoption of this technology and its impact on society are discussed. This examination is done in the context of understanding the balance of power in a negotiation and modeling how this balance will tip with the introduction of automation. An examination of the circumstances when automated negotiation is likely to be adopted is conducted. },
  doi      = {http://dx.doi.org/10.1016/S0160-791X(99)00004-4},
  issn     = {0160-791X},
  keywords = {Negotiation, Automation, Power },
  url      = {http://www.sciencedirect.com/science/article/pii/S0160791X99000044},
}

@Article{Ram12,
  author     = {Ramchurn, Sarvapali D. and Vytelingum, Perukrishnen and Rogers, Alex and Jennings, Nicholas R.},
  title      = {Putting the 'Smarts' into the Smart Grid: A Grand Challenge for Artificial Intelligence},
  journal    = {Commun. ACM},
  year       = {2012},
  volume     = {55},
  number     = {4},
  pages      = {86--97},
  month      = apr,
  acmid      = {2133825},
  address    = {New York, NY, USA},
  doi        = {10.1145/2133806.2133825},
  issn       = {0001-0782},
  issue_date = {April 2012},
  numpages   = {12},
  publisher  = {ACM},
  url        = {http://doi.acm.org/10.1145/2133806.2133825},
}

@Article{Pra10,
  author  = {Pratt, Robert G. and Balducci, Patrick J. and Gerkensmeyer, Clint and Katipamula, Srinivas and Kintner-Meyer, Michael C.W. and Sanquist, Thomas F. and Schneider, Kevin P. and Secrets, Thomas J.},
  title   = {The smart grid: An estimation of the energy and {CO2} benefits},
  journal = {Pacific Northwest National Laboratory},
  year    = {2010},
  pages   = {3--27},
}

@InProceedings{Pre05,
  author    = {Preibusch, S{\"o}ren},
  title     = {Implementing privacy negotiation techniques in e-commerce},
  booktitle = {Seventh IEEE International Conference on E-Commerce Technology (CEC'05)},
  year      = {2005},
  pages     = {387-390},
  month     = {July},
  abstract  = {This paper examines how service providers may resolve the trade-off between their personalization efforts and users' individual privacy concerns through negotiations. The analysis includes the identification of relevant and negotiable privacy dimensions for different usage domains. Based on a formalization of the user's privacy revelation problem, we model the negotiation process as a Bayesian game where the service provider faces different types of users. Finally an extension to P3P is proposed that allows a simple expression and implementation of negotiation processes.},
  doi       = {10.1109/ICECT.2005.53},
  issn      = {2378-1963},
  keywords  = {Bayes methods;data privacy;electronic commerce;game theory;Bayesian game;P3P;e-commerce;privacy negotiation;Autonomous agents;Bayesian methods;Collaboration;Data handling;Data privacy;Game theory;Proposals;Protocols;Recommender systems;Waste materials},
}

@Article{Per15,
  author   = {Perera, Charith and Ranjan, Rajiv and Wang, Lizhe},
  title    = {End-to-End Privacy for Open Big Data Markets},
  journal  = {IEEE Cloud Computing},
  year     = {2015},
  volume   = {2},
  number   = {4},
  pages    = {44-53},
  month    = {July},
  abstract = {Establishing an open data market would require the creation of a data trading model to facilitate exchange of data between different parties in the Internet of Things (IoT) domain. The data collected by IoT products and solutions are expected to be traded in these markets. Data owners will collect data using IoT products and solutions. Data consumers who are interested will negotiate with the data owners to get access to such data. Data captured by IoT products will allow data consumers to further understand the preferences and behaviors of data owners and to generate additional business value using techniques ranging from waste reduction to personalized service offerings. In open data markets, data consumers will be able to give back part of the additional value generated to the data owners. However, privacy becomes a significant issue when data that can be used to derive extremely personal information is being traded. This article discusses why privacy matters in the IoT domain in general and especially in open data markets, and then surveys existing privacy-preserving strategies and design techniques that can be used to facilitate end-to-end privacy for open data markets. It also highlights some of the major research challenges that must be addressed to make the vision of open data markets a reality through ensuring the privacy of stakeholders.},
  doi      = {10.1109/MCC.2015.78},
  issn     = {2325-6095},
  keywords = {Big Data;Internet;Internet of Things;data privacy;electronic data interchange;Internet of Things domain;IoT domain;IoT product;data capture;data consumer;data exchange;data trading model;design technique;end-to-end privacy;open big data markets;open data market;personal information;personalized service offering;privacy-preserving strategy;waste reduction;Big data;Cloud computing;Companies;Data models;Data privacy;Privacy;Sensors;Internet of Things;big data;cloud;privacy;privacy-preserving big data processing},
}


@inproceedings{ANAC2015SAOP,
  title={Alternating offers protocols for multilateral negotiation},
  author={Aydo{\u{g}}an, Reyhan and Festen, David and Hindriks, Koen V. and Jonker, Catholijn M.},
  booktitle = {Modern Approaches to Agent-based Complex Automated Negotiation},
  series={Studies in Computational Intelligence},
  volume={674},
  issn={1860-949X},
  isbn={978-3-319-51561-8},
  publisher={Springer International Publishing},
  year={2016}
}

@techreport{ErasmusEnergyForum2016,
  title={Erasmus Energy Forum 2016 Business Day Report},
  author={Erasmus Center for Future Energy Business},
  year={2016},
  institution={Rotterdam School of Management}
}

@inproceedings{NEST,
  title={Learning from a learning thermostat: lessons for intelligent systems for the home},
  author={Yang, Rayoung and Newman, Mark W.},
  booktitle={Proceedings of the 2013 ACM international joint conference on Pervasive and ubiquitous computing},
  pages={93--102},
  year={2013},
  organization={ACM}
}

@techreport{Pu03,
        title={User-involved preference elicitation},
        author={Pu, Pearl and Faltings, Boi and Torrens, Marc},
        institution={EPFL},
        year={2003}
}

@article{SystematicJobSearch,
  title={Systematic job search and unemployment},
  author={Salop, Steven Charles},
  journal={The Review of Economic Studies},
  volume={40},
  number={2},
  pages={191--201},
  year={1973},
  publisher={JSTOR}
}


@article{UTAGMS,
title = "Ordinal regression revisited: Multiple criteria ranking using a set of additive value functions",
journal = "European Journal of Operational Research",
volume = "191",
number = "2",
pages = "416 - 436",
year = "2008",
issn = "0377-2217",
doi = "https://doi.org/10.1016/j.ejor.2007.08.013",
url = "http://www.sciencedirect.com/science/article/pii/S0377221707008752",
author = "Salvatore Greco and Vincent Mousseau and Roman Slowinski",
keywords = "Multiple criteria ranking",
keywords = "Ordinal regression approach",
keywords = "Additive value function",
abstract = "We present a new method, called UTAGMS, for multiple criteria ranking of alternatives from set A using a set of additive value functions which result from an ordinal regression. The preference information provided by the decision maker is a set of pairwise comparisons on a subset of alternatives ARA, called reference alternatives. The preference model built via ordinal regression is the set of all additive value functions compatible with the preference information. Using this model, one can define two relations in the set A: the necessary weak preference relation which holds for any two alternatives a, b from set A if and only if for all compatible value functions a is preferred to b, and the possible weak preference relation which holds for this pair if and only if for at least one compatible value function a is preferred to b. These relations establish a necessary and a possible ranking of alternatives from A, being, respectively, a partial preorder and a strongly complete relation. The UTAGMS method is intended to be used interactively, with an increasing subset AR and a progressive statement of pairwise comparisons. When no preference information is provided, the necessary weak preference relation is a weak dominance relation, and the possible weak preference relation is a complete relation. Every new pairwise comparison of reference alternatives, for which the dominance relation does not hold, is enriching the necessary relation and it is impoverishing the possible relation, so that they converge with the growth of the preference information. Distinguishing necessary and possible consequences of preference information on the complete set of actions, UTAGMS answers questions of robustness analysis. Moreover, the method can support the decision maker when his/her preference statements cannot be represented in terms of an additive value function. The method is illustrated by an example solved using the UTAGMS software. Some extensions of the method are also presented."
}

@inproceedings{MisrepresentationGame,
 author = {Gratch, Jonathan and Nazari, Zahra and Johnson, Emmanuel},
 title = {The Misrepresentation Game: How to Win at Negotiation While Seeming Like a Nice Guy},
 booktitle = {Proceedings of the 2016 International Conference on Autonomous Agents and Multiagent Systems},
 series = {AAMAS '16},
 year = {2016},
 isbn = {978-1-4503-4239-1},
 location = {Singapore, Singapore},
 pages = {728--737},
 numpages = {10},
 url = {http://dl.acm.org/citation.cfm?id=2936924.2937031},
 acmid = {2937031},
 publisher = {International Foundation for Autonomous Agents and Multiagent Systems},
 address = {Richland, SC},
 keywords = {deception, game theory, negotiation, preference elicitation},
}

@inproceedings{Lu11,
 author = {Lu, Tyler and Boutilier, Craig},
 title = {Robust Approximation and Incremental Elicitation in Voting Protocols},
 booktitle = {Proceedings of the Twenty-Second International Joint Conference on Artificial Intelligence - Volume Volume One},
 series = {IJCAI'11},
 year = {2011},
 isbn = {978-1-57735-513-7},
 location = {Barcelona, Catalonia, Spain},
 pages = {287--293},
 numpages = {7},
 url = {http://dx.doi.org/10.5591/978-1-57735-516-8/IJCAI11-058},
 doi = {10.5591/978-1-57735-516-8/IJCAI11-058},
 acmid = {2283445},
 publisher = {AAAI Press},
} 

@Inbook{Naa14,
author="Naamani-Dery, Lihi
and Golan, Inon
and Kalech, Meir
and Rokach, Lior",
editor="Zarat{\'e}, Pascale
and Kersten, Gregory E.
and Hern{\'a}ndez, Jorge E.",
title="Preference Elicitation for Group Decisions",
bookTitle="Group Decision and Negotiation. A Process-Oriented View: Joint INFORMS-GDN and EWG-DSS International Conference, GDN 2014, Toulouse, France, June 10-13, 2014. Proceedings",
year="2014",
publisher="Springer International Publishing",
address="Cham",
pages="193--200",
abstract="Groups engaged in a mutual activity often need assistance in order to reach a joint decision. However, the group members' personal preferences are often unknown and need to be collected. Querying for preferences can annoy the users. We suggest employing a voting mechanism that finds a winning item under incomplete settings. We present a practical method for eliciting the preferences, so that with a minimal amount of queries a winning item that certainly suits the group can be computed. The heuristic incorporates probabilistic assumptions on the users' preferences and was evaluated on a real world datasets as well as on simulated data, showing a saving in queries to users.",
isbn="978-3-319-07179-4",
doi="10.1007/978-3-319-07179-4_22",
url="https://doi.org/10.1007/978-3-319-07179-4_22"
}

@Inbook{Ill-StructuredNegotiationProblems,
author="Roszkowska, Ewa
and Brzostowski, Jakub
and Wachowicz, Tomasz",
editor="Guo, Peijun
and Pedrycz, Witold",
title="Supporting Ill-Structured Negotiation Problems",
bookTitle="Human-Centric Decision-Making Models for Social Sciences",
year="2014",
publisher="Springer Berlin Heidelberg",
address="Berlin, Heidelberg",
pages="339--367",
abstract="The negotiation is a complex decision-making process in which two or more parties talk with one another in afford to resolve their opposing interests. It can be divided into consecutive stages, namely: pre-negotiation phase involving structuring the problem and the analysis of preferences, the intention phase involving the iterative exchange of offers and counter-offers, and the postoptimization phase aiming at the improvement of the agreement obtained in the intention phase.",
isbn="978-3-642-39307-5",
doi="10.1007/978-3-642-39307-5_14",
url="https://doi.org/10.1007/978-3-642-39307-5_14"
}

@article{HandlingConflict,
title = "Handling conflict between domain descriptions with computer-supported negotiation",
journal = "Knowledge Acquisition",
volume = "3",
number = "3",
pages = "255 - 289",
year = "1991",
issn = "1042-8143",
doi = "https://doi.org/10.1016/1042-8143(91)90007-A",
url = "http://www.sciencedirect.com/science/article/pii/104281439190007A",
author = "Steve Easterbrook",
abstract = "Abstract Conflict is an inevitable part of both knowledge elicitation and system design. People will disagree over how to interpret features of the application domain, what the requirements for a new system are, and how to meet those requirements. Conventional systems analysis techniques avoid such conflicts, making any resolution untraceable and adding to the communication problems. This paper surveys a number of fields which have addressed the problems of conflict resolution. A model of computer-supported negotiation is presented which can be used to address conflicts in systems analysis directly. The model begins with an exploratory phase, in which the conflict is broken down into its components, eliciting the issues which underlie disagreements and criteria to measure their satisfaction. A set of options for possible resolutions are generated using design techniques. Finally, these options are compared to the original issues, and evaluated according to the criteria associated with the issues. The model emphasizes communication, and encourages investigation of other viewpoints. The model has been used to develop a system called Synoptic, which provides a set of tools to support the exploration of conflicts."
}

@Article{Fuj12,
author="Fujita, Katsuhide
and Ito, Takayuki
and Klein, Mark",
title="A Secure and Fair Protocol that Addresses Weaknesses of the Nash Bargaining Solution in Nonlinear Negotiation",
journal="Group Decision and Negotiation",
year="2012",
month="Jan",
day="01",
volume="21",
number="1",
pages="29--47",
abstract="Negotiation with multiple interdependent issues is an important problem since much of real-world negotiation falls into this category. This paper examines the problem that, in such domains, agent utility functions are nonlinear, and thereby can create nonconvex Pareto frontiers. This in turn implies that the Nash Bargaining Solution, which has been viewed as the gold standard for identifying a unique optimal negotiation outcome, does not serve that role in nonlinear domains. In nonlinear domains, unlike linear ones, there can be multiple Nash Bargaining Solutions, and all can be sub-optimal with respect to social welfare and fairness. In this paper, we propose a novel negotiation protocol called SFMP (the Secure and Fair Mediator Protocol) that addresses this challenge, enabling secure multilateral negotiations with fair and pareto-optimal outcomes in nonlinear domains. The protocol works by (1) using nonlinear optimization, combined with a Multi-Party protocol, to find the Pareto front without revealing agent's private utility information, and (2) selecting the agreement from the Pareto set that maximizes a fair division criterion we call approximated fairness. We demonstrate that SFMP is able to find agreements that maximize fairness and social welfare in nonlinear domains, and out-performs (in terms of outcomes and scalability) previously developed nonlinear negotiation protocols.",
issn="1572-9907",
doi="10.1007/s10726-010-9194-6",
url="https://doi.org/10.1007/s10726-010-9194-6"
}

@inproceedings{Mar09a,
 author = {Marsa-Maestre, Ivan and Lopez-Carmona, Miguel A. and Velasco, Juan R. and de la Hoz, Enrique},
 title = {Effective Bidding and Deal Identification for Negotiations in Highly Nonlinear Scenarios},
 booktitle = {Proceedings of The 8th International Conference on Autonomous Agents and Multiagent Systems - Volume 2},
 series = {AAMAS '09},
 year = {2009},
 isbn = {978-0-9817381-7-8},
 location = {Budapest, Hungary},
 pages = {1057--1064},
 numpages = {8},
 url = {http://dl.acm.org/citation.cfm?id=1558109.1558160},
 acmid = {1558160},
 publisher = {International Foundation for Autonomous Agents and Multiagent Systems},
 address = {Richland, SC},
 keywords = {highly-nonlinear utility spaces, multi-agent systems, multi-issue negotiation},
} 

@InProceedings{FastVOI,
  author       = {Mohammad, Yasser and Nakadai, Shinji},
  title        = {FastVOI: Efficient Utility Elicitation During Negotiations},
  booktitle    = {International Conference on Principles and Practice of Multi-Agent Systems},
  year         = {2018},
  pages        = {560--567},
  organization = {Springer},
}

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