• DocumentCode
    1469279
  • Title

    Monte Carlo Beam Search

  • Author

    Cazenave, Tristan

  • Author_Institution
    LAMSADE, Univ. Paris-Dauphine, Paris, France
  • Volume
    4
  • Issue
    1
  • fYear
    2012
  • fDate
    3/1/2012 12:00:00 AM
  • Firstpage
    68
  • Lastpage
    72
  • Abstract
    Monte Carlo tree search is the state of the art for multiple games and for solving puzzles such as Morpion Solitaire. Nested Monte Carlo (NMC) search is a Monte Carlo tree search algorithm that works well for solving puzzles. We propose to enhance NMC search with beam search. We test the algorithm on Morpion Solitaire. Thanks to beam search, our program has been able to match the record score of 82 moves. Monte Carlo beam search achieves better scores in less time than NMC search alone.
  • Keywords
    Monte Carlo methods; computational complexity; computer games; tree searching; Monte Carlo beam search; Monte Carlo tree search algorithm; Morpion solitaire; nested Monte Carlo search; puzzle solving; Computer science; Computers; Games; Learning systems; Monte Carlo methods; Vegetation; Beam search; nested Monte Carlo (NMC) search; puzzle;
  • fLanguage
    English
  • Journal_Title
    Computational Intelligence and AI in Games, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    1943-068X
  • Type

    jour

  • DOI
    10.1109/TCIAIG.2011.2180723
  • Filename
    6169183