• DocumentCode
    1230339
  • Title

    Genetically evolved strategies. Winning by selective processing of the chromosome pool

  • Author

    Sgarbas, Kyriakas ; Fakotakis, Nikos ; Kokkinakis, George

  • Author_Institution
    Dept. of Electr. Eng., Patras Univ., Greece
  • Volume
    14
  • Issue
    1
  • fYear
    1995
  • Firstpage
    36
  • Lastpage
    40
  • Abstract
    Describes how the authors used genetic algorithms (GAs) to make a computer develop its own strategy in playing a simple board game. There are various types of games. John von Neumann and Oskar Morgenstern´s Game Theory classifies games into several categories depending on the number of players involved, the presence or absence of the element of chance, the case that all players receive the same pieces of information or not and the type of payment function. The authors consider two-person zero-sum non-chance perfect-infermation games. Chess and checkers belong to this class
  • Keywords
    game theory; games of skill; genetic algorithms; checkers; chess; genetic algorithms; genetically evolved strategies; selective processing; simple board game; two-person zero-sum nonchance perfect-infermation games; Artificial intelligence; Biological cells; Books; Game theory; Humans; Integrated circuit modeling; Integrated circuit testing; Minimax techniques; Radio access networks;
  • fLanguage
    English
  • Journal_Title
    Potentials, IEEE
  • Publisher
    ieee
  • ISSN
    0278-6648
  • Type

    jour

  • DOI
    10.1109/45.350567
  • Filename
    350567