• DocumentCode
    2446855
  • Title

    On the huge benefit of decisive moves in Monte-Carlo Tree Search algorithms

  • Author

    Teytaud, Fabien ; Teytaud, Olivier

  • Author_Institution
    INRIA, Univ. Paris-Sud, Paris, France
  • fYear
    2010
  • fDate
    18-21 Aug. 2010
  • Firstpage
    359
  • Lastpage
    364
  • Abstract
    Monte-Carlo Tree Search (MCTS) algorithms, including upper confidence Bounds (UCT), have very good results in the most difficult board games, in particular the game of Go. More recently these methods have been successfully introduce in the games of Hex and Havannah. In this paper we will define decisive and anti-decisive moves and show their low computational overhead and high efficiency in MCTS.
  • Keywords
    Monte Carlo methods; decision making; game theory; tree searching; Go; Havannah; Hex; Monte Carlo tree search algorithm; antidecisive move; board game; decisive move; upper confidence bound; Conferences; Games;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computational Intelligence and Games (CIG), 2010 IEEE Symposium on
  • Conference_Location
    Dublin
  • Print_ISBN
    978-1-4244-6295-7
  • Electronic_ISBN
    978-1-4244-6296-4
  • Type

    conf

  • DOI
    10.1109/ITW.2010.5593334
  • Filename
    5593334