Version 83 (modified by mark, 13 years ago) ( diff )

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Literature Survey: Opponent Models

This page provides an overview of the literature survey of Mark Hendrikx. The first Section discusses the researched papers, including a summary
of the relevant details. The second Section provides an overview of all meetings. Finally, the third Section outlines a global planning.
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Papers

TitleA Framework for Building Intelligent SLA Negotiation Strategies under Time Constraints
Author(s)G.C. Silaghi, L.D. Şerban and C.M. Litan
Cited-
Subject(s)
Summary
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BibtexLink
Cites seenYes


TitleA Framework for Multi-agent Electronic Marketplaces: Analysis and Classification of Existing Systems
Author(s)K. Kurbel and I. Loutchko
Cited25
Subject(s)
Summary
Relevance
BibtexLink
Cites seenYes


TitleA Machine Learning Approach to Automated Negotiation and Prospects for Electronic Commerce
Author(s)J.R. Oliver
Cited198
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Summary
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BibtexLink
Cites seen


TitleAgentFSEGA - Time Constrained Reasoning Model for Bilateral Multi-Issue Negotiation
Author(s)L.D. Serban, G.C. Silaghi, and C.M. Litan
Cited-
Subject(s)
Summary
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BibtexX
Cites seenYes


TitleAgents that Acquire Negotiation Strategies Using a Game Theoretic Learning Theory
Author(s)N. Eiji Nawa
Cited2
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BibtexLink
Cites seen


TitleAn Adaptive Learning Method in Automated Negotiation Based on Artificial Neural Network
Author(s)Z. Zeng, B. Meng, Y. Zeng
Cited4
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TitleAn Architecture for Negotiating Agents that Learn
Author(s)H.H. Bui, S. Venkatesh, and D. Kieronska
Cited2
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Summary
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BibtexLink
Cites seenYes


TitleAn Automated Agent for Bilateral Negotiation with Bounded Rational Agents with Incomplete Information
Author(s)R. Lin, S. Kraus, J. Wilkenfeld, J. Barry
Cited23
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Summary
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BibtexLink
Cites seen


TitleAn Evolutionairy Learning Approach for Adaptive Negotiation Agents
Author(s)R.Y.K. Lau, M. Tang, O. Wong, S.W. Milliner
Cited19
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Summary
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BibtexLink
Cites seen


TitleAnalysis of Negotiation Dynamics
Author(s)K. Hindriks, C.M. Jonker, D. Tykhonov
Cited5
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Summary
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BibtexLink
Cites seenYes


TitleAnticipating Agent's Negotiation Strategies in an E-marketplace Using Belief Models
Author(s)F. Teuteberg, K. Kurbel
Cited11
Subject(s)
Summary
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BibtexLink
Cites seenYes


TitleAutomated Multi-Attribute Negotiation with Efficient Use of Incomplete Preference Information
Author(s)C. Jonker and V. Robu
Cited44
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BibtexLink
Cites seen


TitleBayesian Learning in Bilateral Multi-issue Negotiation and its Application in MAS-based Electronic Commerce
Author(s)J. Li, Y. Cao
Cited6
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Summary
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BibtexLink
Cites seenYes


TitleBayesian Learning in Negotiation
Author(s)D. Zeng, K. Sycara
Cited355
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Summary
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BibtexLink
Cites seenYes


TitleBenefits of Learning in Negotiation
Author(s)D. Zeng, K. Sycara
Cited116
Subject(s)Benefits of learning, Bayesian learning, reservation values
Summary Growing interest in e-commerce motivates research in automated negotiation. Building intelligent negotiation agents is still
emerging. In contrast to most negotiation models, sequential decision model allows for learning. Learning can help understand
human behaviour, but can also result in better results for the learning party. Bayesian learning of reservation
values can be used to determine the zone of agreement for an issue based on the domain knowledge and bidding interactions.
Concluding for one-issue, learning positively influences bargaining quality, number of exchanged proposals,
and leads to a better compromise if both learn. Learning works always works better in the proposed case.
Relevance8. Strong example of Bayesian learning
BibtexLink
Cites seenYes


TitleBilateral Negotiation with Incomplete and Uncertain Information: A Decision-Theoretic Approach Using a Model of the Opponent
Author(s)C. Mudgal, J. Vassileva
Cited42
Subject(s)
Summary
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Bibtex
Cites seenYes


TitleComparing Equilibria for Game-Theoretic and Evolutionary Bargaining Models
Author(s)S. Fatima, M. Wooldridge, N.R. Jennings
Cited21
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Summary
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BibtexLink
Cites seen


TitleCompromising Strategy based on Estimated Maximum Utility for Automated Negotiating Agents
Author(s)S. Kawaguchi, K. Fujita, T. Ito
Cited-
Subject(s)
Summary
Relevance
BibtexX
Cites seenYes


TitleDetermining Succesful Negotiation Strategies: An Evolutionary Approach
Author(s)N. Matos, C. Sierra, N.R. Jennings
Cited149
Subject(s)
Summary
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BibtexLink
Cites seen


TitleFacing the Challenge of Human-Agent Negotiations via Effective General Opponent Modeling
Author(s)Y. Oshrat, R. Lin, S. Kraus
Cited19
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Summary
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BibtexLink
Cites seenYes


TitleGenetic Algorithms for Automated Negotiations: A FSM-Based Application Approach
Author(s)M.T. Tu, E. Wolff, W. Lamersdorf
Cited37
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BibtexLink
Cites seen


TitleIAMhaggler: A Negotiation Agent for Complex Environments
Author(s)C.R. Williams, V. Robu, E.H. Gerding, and N.R. Jennings
Cited-
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Summary
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BibtexLink
Cites seenYes


TitleInferring implicit preferences from negotiation actions
Author(s)A. Restificar and P. Haddawy
Cited10
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BibtexLink
Cites seenYes


TitleIntegration of Learning, Situational Power and Goal Constraints Into Time-Dependent Electronic Negotiation Agents
Author(s)W.W.H. Mok
Cited-
Subject(s)
Summary
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BibtexLink
Cites seenYes


TitleLearning Algorithms for Single-instance Electronic Negotiations using the Time-dependent Behavioral Tactic
Author(s)W.W.H Mok and R.P. Sundarraj
Cited17
Subject(s)
Summary
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BibtexLink
Cites seenYes


TitleLearning an Agent's Utility Function by Observing Behavior
Author(s)U. Chajewska, D. Koller, D. Ormoneit
Cited54
Subject(s)
Summary
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BibtexLink
Cites seenYes


TitleLearning an Opponent's Preferences to Make Effective Multi-Issue Negotiation Trade-Offs
Author(s)R.M. Coehoorn, N.R. Jennings
Cited78
Subject(s)KDE Learning, Negotiation model, Concession based strategy
Summary Effective and efficient multi-issue negotiation requires an agent to have some indication of it's opponent's preferences
over the issues in the domain. Kernel Density Estimation (KDE) is used to estimate the weight attached to different issues
by different agents. It is assumed that if the value of an issue increases, that this is positive for one agent, and negative
for the other. No assumptions about relation between time, negotiation history and issue-weight are required, in contrast
to Bayesian learning. The difference between concessive (counter)offers is used to estimate the weights of the issues
(assumption: stronger concessions are made later on in the negotiation). Faratin's hill climbing algorithm augmented with KDE is
used to propose the next bid. KDE proved succesful on the used negotiation model. Future works entails testing the approach
against different opponent strategies and extending the approach to other negotiation models (see assumption in summary).
Relevance9. KDE learning described in detail. Strong related work section
BibtexLink
Cites seenYes


TitleLearning Opponents' Preferences in Multi-Object Automated Negotiation
Author(s)S. Buffett and B. Spencer
Cited18
Subject(s)
Summary
Relevance
BibtexLink
Cites seenYes


TitleLearning other Agents' Preferences in Multiagent Negotiation using the Bayesian Classifier.
Author(s)H.H. Bui, D. Kieronska, S. Venkatesh
Cited29
Subject(s)
Summary
Relevance
BibtexLink
Cites seenYes


TitleLearning to Select Negotiation Strategies in Multi-Agent Meeting Scheduling
Author(s)E. Crawford and M. Veleso
Cited21
Subject(s)
Summary
Relevance
BibtexLink
Cites seen


TitleModelling Agents Behaviour in Automated Negotiation
Author(s)C. Hou
Cited10
Subject(s)
Summary
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BibtexLink
Cites seen


TitleModeling Opponent Decision in Repeated One-shot Negotiations
Author(s)S.Saha, A. Biswas, S. Sen
Cited26
Subject(s)
Summary
Relevance
BibtexLink
Cites seenYes


TitleNegotiating agents that learn about others' preferences
Author(s)H.H. Bui, D. Kieronska and S. Venkatesh
Cited5
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Summary
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BibtexLink
Cites seen


TitleNegotiation Decision Functions for Autonomous Agent
Author(s)P. Faratin, C. Sierra, N.R. Jennings
Cited718
Subject(s)
Summary
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BibtexLink
Cites seenYes


TitleNegotiation Dynamics: Analysis, Concession Tactics, and Outcomes
Author(s)K. Hindriks, C.M. Jonker, D. Tykhonov
Cited7
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Summary
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BibtexLink
Cites seenYes


TitleOn-Line Incremental Learning in Bilateral Multi-Issue Negotiation
Author(s)V. Soo, C. Hung
Cited18
Subject(s)
Summary
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BibtexLink
Cites seenYes


TitleOn Learning Negotiation Strategies by Artificial Adaptive Agents in Environments of Incomplete Information
Author(s)J.R. Oliver
Cited6
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Summary
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BibtexLink
Cites seen


TitleOpponent Model Estimation in Bilateral Multi-issue Negotiation
Author(s)N. van Galen Last
Cited-
Subject(s)
Summary
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BibtexX
Cites seenYes


TitleOpponent Modelling in Automated Multi-Issue Negotiation Using Bayesian Learning
Author(s)K. Hindriks, D. Tykhonov
Cited33
Subject(s)
Summary
Relevance
BibtexLink
Cites seenYes


TitleOptimal negotiation strategies for agents with incomplete information
Author(s)S.S. Fatima, M. Wooldridge and N.R. Jennings
Cited88
Subject(s)
Summary
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BibtexLink
Cites seenYes


TitlePredicting Agents Tactics in Automated Negotiation
Author(s)C. Hou
Cited12
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Summary
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BibtexLink
Cites seen


TitlePredicting partner's behaviour in agent negotiation
Author(s)J. Brzostowski, R. Kowalczyk
Cited16
Subject(s)
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Relevance
Bibtexhttp://scholar.google.nl/scholar.bib?q=info:3MifmJepz_4J:scholar.google.com/&output=citation&hl=nl&as_sdt=0,5&ct=citation&cd=0 Link
Cites seen


TitleThe Benefits of Opponent Models in Negotiation
Author(s)K. Hindriks, C.M. Jonker, D. Tykhonov
Cited-
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Summary
Relevance
BibtexLink
Cites seenYes


TitleThe First Automated Negotiating Agents Competition (ANAC 2010)
Author(s)T. Baarslag, K. Hindriks, C. Jonker, S. Kraus, R. Lin
Cited-
Subject(s)ANAC, overview multiple agents, opponent models, acceptance conditions
SummaryThe ANAC competition models bilateral multi-issue closed negotiations and provides a benchmark for negotiation agents.
Opponent models can also be used to identify the type of strategy of the opponent. Interesting agents for further analysis
are: IAM(crazy)Haggler, FSEGA (profile learning), and Agent Smith. Issues can be predicatable, which means that they
have a logical order, or unpredicatable, such as colors. This paper also includes acceptance conditions.
Relevance5, too global, however interesting citations
BibtexLink
Cites seenYes


TitleTowards a Quality Assessment Method for Learning Preference Profiles in Negotiation
Author(s)K.V. Hindriks and D. Tykhonov
Cited6
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Summary
Relevance
BibtexLink
Cites seenYes


TitleUsing Similarity Criteria to Make Issue Trade-offs in Automated Negotiations
Author(s)P. Faratin, C. Sierra, N.R. Jennings
Cited367
Subject(s)
Summary
Relevance
BibtexLink
Cites seenYes


TitleYushu: a Heuristic-Based Agent for Automated Negotiating Competition
Author(s)B. An and V. Lesser
Cited-
Subject(s)
Summary
Relevance
BibtexX
Cites seenYes


Meetings

Onaangekondigde Meeting (20/04/11)

In verband met de conferentie in Taiwan is in overleg met Tim besproken dat we waarschijnlijk meer tijd nodig gaan hebben voor ons paper.
Dit houdt in dat de deadline is verschoven naar begin september. Als persoonlijk doel heb ik gesteld om eind juni een kladversie te hebben.

Planning

26/04/11Meeste interessante papers gevonden
28/04/11 - 09/05-11Conferentie bijwonen en op laag tempo doorwerken
23/05/11Alle papers samengevat
26/05/11Opzet taxonomie
29/06/11Kladversie paper af

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