• DocumentCode
    2431414
  • Title

    Competitive co-evolution based game-strategy acquisition with packaging strategies method

  • Author

    Nerome, Moeko ; Yamada, Koji ; Endo, Satoshi ; Miyagi, Hayao

  • Author_Institution
    Dept. of Inf. Eng., Ryukyus Univ., Okinawa, Japan
  • Volume
    5
  • fYear
    1997
  • fDate
    12-15 Oct 1997
  • Firstpage
    4418
  • Abstract
    One of the important issues in the field of artificial intelligence is to develop the method on the acquisition of game strategy. In this paper, our purpose is the acquisition of game-strategy by using competitive co-evolution approach as a search method. The competitive co-evolution is the mechanism of the interactive improvement. However, in practical game, it isn´t easy to acquire the best strategy by applying competitive co-evolution model, because of complex strategy space. Therefore, to design the acquisition system of stronger game strategy, we propose an improved competitive co-evolution model that introduces the concept of “package” as a set of good strategies. Creating the good package needs to collect some good strategies to defeat various kinds of the opponents. To show the efficiency of this algorithm, we apply it to a complicated game
  • Keywords
    artificial intelligence; competitive algorithms; game theory; unsupervised learning; artificial intelligence; competitive co-evolution based game-strategy acquisition; complicated game; packaging strategies method; Artificial intelligence; Packaging; Sampling methods; Search methods;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Systems, Man, and Cybernetics, 1997. Computational Cybernetics and Simulation., 1997 IEEE International Conference on
  • Conference_Location
    Orlando, FL
  • ISSN
    1062-922X
  • Print_ISBN
    0-7803-4053-1
  • Type

    conf

  • DOI
    10.1109/ICSMC.1997.637519
  • Filename
    637519