• DocumentCode
    2328649
  • Title

    Evolving group strategies for IPD

  • Author

    Hingston, Philip

  • Author_Institution
    Sch. of Comput. Sci. & Security, Edith Cowan Univ., Perth, WA, Australia
  • fYear
    2010
  • fDate
    18-23 July 2010
  • Firstpage
    1
  • Lastpage
    7
  • Abstract
    The Iterated Prisoners Dilemma (IPD) is often used to model cooperation between self-interested agents. In an earlier study, we introduced a framework using IPD to study the effects of species-level competition on the evolution of cooperative behaviour. In this paper, we extend the previous work, using co-evolutionary simulations of interactions between species of IPD-playing agents to investigate how group strategies may evolve. We find that the ability to cooperate more with agents of the same species greatly increases the ferocity of competition between species.
  • Keywords
    competitive algorithms; evolution (biological); game theory; group theory; IPD playing agent; coevolutionary simulation; cooperative behaviour; group strategies; iterated prisoners dilemma; species level competition; Bioinformatics; Biological system modeling; Computational modeling; Evolution (biology); Games; Genomics; Organisms;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Evolutionary Computation (CEC), 2010 IEEE Congress on
  • Conference_Location
    Barcelona
  • Print_ISBN
    978-1-4244-6909-3
  • Type

    conf

  • DOI
    10.1109/CEC.2010.5586197
  • Filename
    5586197