Score Bounded Monte-Carlo Tree Search

被引:0
|
作者
Cazenave, Tristan [1 ]
Saffidine, Abdallah [1 ]
机构
[1] Univ Paris 09, LAMSADE, Paris, France
来源
COMPUTERS AND GAMES | 2011年 / 6515卷
关键词
D O I
暂无
中图分类号
TP301 [理论、方法];
学科分类号
081202 ;
摘要
Monte-Carlo Tree Search (MCTS) is a successful algorithm used in many state of the art game engines. We propose to improve a MCTS solver when a game has more than two outcomes. It is for example the case in games that can end in draw positions. In this case it improves significantly a MCTS solver to take into account bounds on the possible scores of a node in order to select the nodes to explore. We apply our algorithm to solving Seki in the game of Go and to Connect Four.
引用
收藏
页码:93 / 104
页数:12
相关论文
共 50 条
  • [21] Converging to a Player Model In Monte-Carlo Tree Search
    Sarratt, Trevor
    Pynadath, David V.
    Jhala, Arnav
    2014 IEEE CONFERENCE ON COMPUTATIONAL INTELLIGENCE AND GAMES (CIG), 2014,
  • [22] AIs for Dominion Using Monte-Carlo Tree Search
    Tollisen, Robin
    Jansen, Jon Vegard
    Goodwin, Morten
    Glimsdal, Sondre
    CURRENT APPROACHES IN APPLIED ARTIFICIAL INTELLIGENCE, 2015, 9101 : 43 - 52
  • [23] Parallel Monte-Carlo Tree Search with Simulation Servers
    Kato, Hideki
    Takeuchi, Ikuo
    INTERNATIONAL CONFERENCE ON TECHNOLOGIES AND APPLICATIONS OF ARTIFICIAL INTELLIGENCE (TAAI 2010), 2010, : 491 - 498
  • [24] A SHOGI PROGRAM BASED ON MONTE-CARLO TREE SEARCH
    Sato, Yoshikuni
    Takahashi, Daisuke
    Grimbergen, Reijer
    ICGA JOURNAL, 2010, 33 (02) : 80 - 92
  • [25] CROSS-ENTROPY FOR MONTE-CARLO TREE SEARCH
    Chaslot, Guillaume M. J. B.
    Winands, Mark H. M.
    Szita, Istvan
    van den Herik, H. Jaap
    ICGA JOURNAL, 2008, 31 (03) : 145 - 156
  • [26] Monte-Carlo Tree Search Parallelisation for Computer Go
    van Niekerk, Francois
    Kroon, Steve
    van Rooyen, Gert-Jan
    Inggs, Cornelia P.
    PROCEEDINGS OF THE SOUTH AFRICAN INSTITUTE FOR COMPUTER SCIENTISTS AND INFORMATION TECHNOLOGISTS CONFERENCE, 2012, : 129 - 138
  • [27] Can Monte-Carlo Tree Search learn to sacrifice?
    Nathan Companez
    Aldeida Aleti
    Journal of Heuristics, 2016, 22 : 783 - 813
  • [28] Monte-Carlo Tree Search for the Maximum Satisfiability Problem
    Goffinet, Jack
    Ramanujan, Raghuram
    PRINCIPLES AND PRACTICE OF CONSTRAINT PROGRAMMING, CP 2016, 2016, 9892 : 251 - 267
  • [29] Parallel Monte-Carlo Tree Search for HPC Systems
    Graf, Tobias
    Lorenz, Ulf
    Platzner, Marco
    Schaefers, Lars
    EURO-PAR 2011 PARALLEL PROCESSING, PT 2, 2011, 6853 : 365 - 376
  • [30] Can Monte-Carlo Tree Search learn to sacrifice?
    Companez, Nathan
    Aleti, Aldeida
    JOURNAL OF HEURISTICS, 2016, 22 (06) : 783 - 813