• DocumentCode
    1635470
  • Title

    Symmetric networks foster to evolve desirable turn-taking rules in dispersion games

  • Author

    Namatame, Akira ; Sato, Hiroshi

  • Author_Institution
    Comput. Sci. Dept., Nat. Defense Acad., Yokosuka
  • fYear
    2009
  • Firstpage
    514
  • Lastpage
    521
  • Abstract
    Using a game-theoretic model combined with the evolutionary model, we investigate the conditions under which the desirable interaction rules will evolve and sustain in various social interaction settings. The direction of the research to come is to understand how the interaction structure, the network topology, determines the path of evolutionary dynamics. For the emergence of desirable outcomes at the macroscopic level, the patterns of social interaction are critical. We find that the efficient and fair outcome emerges relatively quickly in symmetric networks where each agent plays the game with the same number of players. In symmetric networks, agents appear to easily recognize the possibility of a coordinated turn-taking behaviour or alternating reciprocity as a means to generate an efficient and fair outcome.
  • Keywords
    evolutionary computation; game theory; learning (artificial intelligence); multi-agent systems; topology; EVOLUTIONARY game theory; agent interaction; desirable interaction rule; dispersion game theoretic model; learning algorithm; network topology; social interaction; symmetric network foster; turn-taking rule; Arm; Computer simulation; Game theory; Genetic algorithms; Genetic mutations; Learning; Network topology; Thin film transistors;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Evolutionary Computation, 2009. CEC '09. IEEE Congress on
  • Conference_Location
    Trondheim
  • Print_ISBN
    978-1-4244-2958-5
  • Electronic_ISBN
    978-1-4244-2959-2
  • Type

    conf

  • DOI
    10.1109/CEC.2009.4982989
  • Filename
    4982989