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Strategic Coalition for Improving Generalization Ability of Multi-agent with Evolutionary Learning  

양승룡 (연세대학교 컴퓨터학과)
조성배 (연세대학교 컴퓨터학과)
Publication Information
Journal of KIISE:Software and Applications / v.31, no.2, 2004 , pp. 101-110 More about this Journal
Abstract
In dynamic systems, such as social and economic systems, complex interactions emerge among its members. In that case, their behaviors become adaptive according to Changing environment. In many cases, an individual's behaviors can be modeled by a stimulus-response system in a dynamic environment. In this paper, we use the Iterated Prisoner's Dilemma (IPD) game, which is simple yet capable of dealing with complex problems, to model the dynamic systems. We propose strategic coalition consisting of many agents and simulate their emergence in a co-evolutionary learning environment. Also we introduce the concept of confidence for agents in a coalition and show how such confidences help to improve the generalization ability of the whole coalition. Experimental results are presented to demonstrate that co-evolutionary learning with coalitions and confidence allows better performing strategies that generalize well.
Keywords
IPD game; Strategic Coalition; Evolutionary Learning; Multi-agent;
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Times Cited By KSCI : 1  (Citation Analysis)
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