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