• DocumentCode
    1400970
  • Title

    Current Frontiers in Computer Go

  • Author

    Rimmel, Arpad ; Teytaud, Olivier ; Lee, Chang-Shing ; Yen, Shi-Jim ; Wang, Mei-Hui ; Tsai, Shang-Rong

  • Author_Institution
    LRI, Univ. Paris-Sud, Orsay, France
  • Volume
    2
  • Issue
    4
  • fYear
    2010
  • Firstpage
    229
  • Lastpage
    238
  • Abstract
    This paper presents the recent technical advances in Monte Carlo tree search (MCTS) for the game of Go, shows the many similarities and the rare differences between the current best programs, and reports the results of the Computer Go event organized at the 2009 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE2009), in which four main Go programs played against top level humans. We see that in 9 × 9, computers are very close to the best human level, and can be improved easily for the opening book; whereas in 19 × 19, handicap 7 is not enough for the computers to win against top level professional players, due to some clearly understood (but not solved) weaknesses of the current algorithms. Applications far from the game of Go are also cited. Importantly, the first ever win of a computer against a 9th Dan professional player in 9 × 9 Go occurred in this event.
  • Keywords
    Monte Carlo methods; computer games; fuzzy systems; game theory; tree searching; FUZZ IEEE 2009; IEEE international conference; Monte Carlo tree search; computer go; fuzzy system; Algorithm design and analysis; Decision trees; Game theory; Games; Monte Carlo methods; Game of Go; Monte Carlo tree search (MCTS); upper confidence;
  • fLanguage
    English
  • Journal_Title
    Computational Intelligence and AI in Games, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    1943-068X
  • Type

    jour

  • DOI
    10.1109/TCIAIG.2010.2098876
  • Filename
    5664776