Changes between Version 104 and Version 105 of OpponentModels

Timestamp:

05/10/11 17:20:11 (14 years ago)

Author:

mark

Comment:

--

OpponentModels

@@ -143 +143 @@
 ||'''Author(s)'''||C. Jonker and V. Robu||
 ||'''Cited'''||44||
-||'''Subject(s)'''||Model for taking learning and initial information into account||
+||'''Subject(s)'''||Mechanism for taking learning and initial information into account in a standard bilateral negotiation model||
 ||'''Summary'''||The classic technique for negotiation with undisclosed preferences is to use a mediator, however[[BR]] can we be sure that he is impartial? The negotiation strategy discussed is for billeteral multi-issue[[BR]] negotiation. A decreasing util curve is considered. A bid is calculated to fit the current [[BR]]util. Each issue has a seperate parameter such that more or less concession can be made on [[BR]]certain issues. General tolerance determines the general speed of concession. For each issue[[BR]] for the opponent bid and new calculated bid it is considered how much concession is made [[BR]]towards the opponent bid based on the configuration tolerance for each issue. This full [[BR]]formula depends on the weights of the opponent, which have to be estimated. The weights for each [[BR]]attribute can be estimated by comparing the distance between attributes for an issue in [[BR]]sequential bids and using this distance to mark the importance of an attribute. This last [[BR]]step is domain dependent. Concluding, the technique works, but requires tuning for the domain[[BR]] and assumes that the other agent plays a more or less similiar concession based technique. ||
-||'''Relevance'''||||
+||'''Relevance'''||4, domain dependent opponent modelling approach for learning ordering of attributes||
 ||'''Bibtex'''||[http://scholar.google.nl/scholar.bib?q=info:fSLXt9dFf4kJ:scholar.google.com/&output=citation&hl=nl&as_sdt=0,5&ct=citation&cd=0 Link]||
 ||'''Cites seen'''||Yes||