Changes between Version 105 and Version 106 of OpponentModels

Timestamp:

05/10/11 19:29:59 (14 years ago)

Author:

mark

Comment:

--

OpponentModels

@@ -253 +253 @@
 ||'''Author(s)'''||C.R. Williams, V. Robu, E.H. Gerding, and N.R. Jennings||
 ||'''Cited'''||-||
-||'''Subject(s)'''||||
-||'''Summary'''||||
-||'''Relevance'''||||
+||'''Subject(s)'''||ANAC, Pareto search, Bayes' rule||
+||'''Summary'''||IAMhaggler first determines the discount factor of the opponent by using non-linear regression. Next, the found curve[[BR]] is discounted to find the opponent bid curve. Next, the maximum is found on the opponent curve, and an [[BR]] appropriate curve is plotted for the own utility curve. For domains without unordered issues Pareto-search is [[BR]] used to determine all possible bids matching an utility. Next, it is determined which bid is the closest to the best[[BR]]  received opponent bid by using the euclidean distance. For domains with unordered issues, each [[BR]] unorderded value is varied, after which the possible bids are determined which satisfy the utility. Finally, using Bayes' [[BR]] rule for opponent modelling, the best possible bid for the opponent is chosen. ||
+||'''Relevance'''||8, beautifull strategy||
 ||'''Bibtex'''||[http://scholar.google.nl/scholar.bib?q=info:dXychgQCiFMJ:scholar.google.com/&output=citation&hl=nl&as_sdt=0,5&ct=citation&cd=0 Link]||
 ||'''Cites seen'''||Yes||