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
Link To Document :
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