Exploiting coalition in co-evolutionary learning

Yeon-Gyu SEO, Sung-Bae CHO, Xin YAO

Research output: Book Chapters | Papers in Conference ProceedingsConference paper (refereed)Researchpeer-review

11 Citations (Scopus)

Abstract

Adaptive behaviors often emerge through interactions between adjacent neighbors in dynamic systems, such as social and economic systems. 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 a dynamic system such as social or economic systems. We investigate coalitions consisting of many players and their emergence in a co-evolutionary learning environment. We introduce the concept of confidence for players in a coalition and show how such confidences help to improve the generalization ability of the whole coalition. Experimental results will be presented to demonstrate that co-evolutionary learning with coalitions and player confidences can produce IPD game-playing strategies that generalize well.
Original languageEnglish
Title of host publicationProceedings of the IEEE Conference on Evolutionary Computation, ICEC
Pages1268-1275
Number of pages8
Volume2
Publication statusPublished - 2000
Externally publishedYes

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