• DocumentCode
    2650467
  • Title

    The research of pattern symmetry problem in learning in computer Go

  • Author

    Xin, Wei ; Yinglong, Sun ; Hui, Yang ; Jiao, Wang

  • Author_Institution
    Coll. of Inf. Sci. & Eng., Northeastern Univ., Shenyang, China
  • fYear
    2012
  • fDate
    23-25 May 2012
  • Firstpage
    3301
  • Lastpage
    3306
  • Abstract
    Pattern is a very effective approach to improve the Monte-Carlo tree search. Due to the limitation of affordable memory space, the two typical pattern sizes are 3*3 or 4*4. Pattern libraries may be constructed by hand-craft or machine learning, which are all suffered from pattern symmetry problem. This paper elaborates and classifies the pattern symmetry problem in 3*3-pattern and 4*4-pattern, and introduces the solution for solving it in learning procedure. The experimental results show that the solution is effective and the learning results are improved through solving pattern symmetry problem.
  • Keywords
    Monte Carlo methods; computer games; learning (artificial intelligence); pattern classification; tree searching; Monte Carlo tree search; computer Go; learning procedure; pattern libraries; pattern sizes; pattern symmetry problem classification; Bayesian methods; Color; Computational modeling; Computers; Encoding; Games; Libraries; Learning; Monte-Carlo Go; Pattern; UCT;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Control and Decision Conference (CCDC), 2012 24th Chinese
  • Conference_Location
    Taiyuan
  • Print_ISBN
    978-1-4577-2073-4
  • Type

    conf

  • DOI
    10.1109/CCDC.2012.6243085
  • Filename
    6243085