Co-evolution of Optimal Agents for the Alternating Offers Bargaining Game

被引:0
|
作者
Chandra, Arjun [1 ]
Oliveto, Pietro Simone [1 ]
Yao, Xin [1 ]
机构
[1] Univ Birmingham, CERCIA, Sch Comp Sci, Birmingham B15 2TT, W Midlands, England
基金
英国工程与自然科学研究理事会;
关键词
D O I
暂无
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Bargaining, as an instance of sequential games, is a widely studied problem in game theory, experimental and computational economics. We consider the problem of evolving computational agents with optimal (Subgame Perfect Equilibrium) strategies for the Alternating Offers Bargaining Came. Previous work co-evolving agents for this problem has argued that it is not possible to achieve optimal agents at the end of the co-evolutionary process due to the myopic properties of the evolutionary agents. Emphasising the notion of a co-evolutionary solution concept, we show that this conclusion is mis-leading and present a co-evolutionary algorithm that evolves optimal strategies for the bargaining game with one round. We conclude by explaining why, using previous evaluation procedures and strategy representations, the algorithm is not able to converge to optimal strategies for games with more rounds.
引用
收藏
页码:61 / 70
页数:10
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