Changes between Version 98 and Version 99 of OpponentModels

Timestamp:

05/10/11 11:22:27 (14 years ago)

Author:

mark

Comment:

--

OpponentModels

@@ -50 +50 @@
 ||'''Author(s)'''||L.D. Serban, G.C. Silaghi, and C.M. Litan||
 ||'''Cited'''||-||
-||'''Subject(s)'''||||
+||'''Subject(s)'''||Learning issue utility curves by Bayesian learning; Learning issue ordering||
 ||'''Summary'''||The opponent model of FSEGA tries to approximate the ordering of the issues and the utility function of each issue by using Bayesian[[BR]] learning. Each value in an issue is imagined as approximating one of the three basic functions (downhill, uphill, triangular). Using[[BR]] the Bayesian formula, each hypothesis for a value is updated. Finally the hypothesis are combined based on their likelihood[[BR]] to determine the final form of the utility function for each value in the issue; combining these results in the utility function for[[BR]] an issue. Finally, the bidding strategy uses isocurves and the opponent model to increase acceptance.||
-||'''Relevance'''||||
+||'''Relevance'''||8||
 ||'''Bibtex'''||X||
 ||'''Cites seen'''||Yes||