Exploiting coalition in co-evolutionary learning

Yeon Gyu Seo, Sung Bae Cho, Xin Yao

Research output: Contribution to conferencePaper

10 Citations (Scopus)


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
Number of pages8
Publication statusPublished - 2000 Dec 3
EventProceedings of the 2000 Congress on Evolutionary Computation - California, CA, USA
Duration: 2000 Jul 162000 Jul 19


OtherProceedings of the 2000 Congress on Evolutionary Computation
CityCalifornia, CA, USA

All Science Journal Classification (ASJC) codes

  • Engineering(all)
  • Computer Science(all)
  • Computational Theory and Mathematics

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    Seo, Y. G., Cho, S. B., & Yao, X. (2000). Exploiting coalition in co-evolutionary learning. 1268-1275. Paper presented at Proceedings of the 2000 Congress on Evolutionary Computation, California, CA, USA, .