• DocumentCode
    356802
  • Title

    Playing the Rock-Paper-Scissors game with a genetic algorithm

  • Author

    Ali, F.F. ; Nakao, Z. ; Wei, Yen

  • Author_Institution
    Dept. of Manage. & Inf. Syst., Meio Univ., Okinawa, Japan
  • Volume
    1
  • fYear
    2000
  • fDate
    2000
  • Firstpage
    741
  • Abstract
    This paper describes a strategy to follow whilst playing the Rock-Paper-Scissors game. Instead of making a biased decision, a rule is adopted where the outcomes of the game from the last few turns are observed and then a deterministic decision is made. Such a strategy is encoded into a genetic string and a genetic algorithm works on a population of such strings. Good strings are produced in later generations. Such a strategy is found to be successful, and its efficiency is demonstrated by testing the strategy against both systematic and human strategies
  • Keywords
    game theory; genetic algorithms; cooperative short memory behavior; deterministic decision; evolutionary systems; game theory; genetic algorithm; genetic string; historical behavior; human strategies; opponent; outcomes; rock-paper-scissors game; Biological system modeling; Engineering management; Game theory; Genetic algorithms; Genetic engineering; History; Humans; Information management; Management information systems; System testing;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Evolutionary Computation, 2000. Proceedings of the 2000 Congress on
  • Conference_Location
    La Jolla, CA
  • Print_ISBN
    0-7803-6375-2
  • Type

    conf

  • DOI
    10.1109/CEC.2000.870372
  • Filename
    870372