• DocumentCode
    2669202
  • Title

    A genetic search method for multi-player game playing

  • Author

    Hong, Tzung-Pei ; Huang, Ke-Yuan ; Lin, Wen-Yang

  • Author_Institution
    Dept. of Inf. Manage., I-Shou Univ., Kaohsiung, Taiwan
  • Volume
    5
  • fYear
    2000
  • fDate
    2000
  • Firstpage
    3858
  • Abstract
    It is well known that when exploring a game tree, the deeper the depth, the more accurate the move prediction but greater temporal and spatial expansion is required. How to explore the game tree deeper is a great challenge in such research. In T.P. Hong et al (Int. Conf. on Evolutionary Computation, Anchorage, Alaska, USA, p.690-4, 1998), we proposed a genetic algorithm-based search method for two-player games. In this paper, we generalize that method to solve multi-player game-search problems. We propose a genetic algorithm-based approach that can find good next moves in multi-player games without the requirement for great temporal and spatial expansion
  • Keywords
    game theory; games of skill; genetic algorithms; search problems; evolutionary computation; game tree; game-search problems; genetic algorithm; genetic search method; good next moves; multiplayer game playing; Artificial intelligence; Decision trees; Genetics; Humans; Information management; Machine learning; Machine learning algorithms; Minimax techniques; Performance evaluation; Search methods;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Systems, Man, and Cybernetics, 2000 IEEE International Conference on
  • Conference_Location
    Nashville, TN
  • ISSN
    1062-922X
  • Print_ISBN
    0-7803-6583-6
  • Type

    conf

  • DOI
    10.1109/ICSMC.2000.886612
  • Filename
    886612