On the Huge Benefit of Decisive Moves in Monte-Carlo Tree Search Algorithms - Inria - Institut national de recherche en sciences et technologies du numérique
Communication Dans Un Congrès Année : 2010

On the Huge Benefit of Decisive Moves in Monte-Carlo Tree Search Algorithms

Résumé

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.
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Dates et versions

inria-00495078 , version 1 (25-06-2010)

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  • HAL Id : inria-00495078 , version 1

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Fabien Teytaud, Olivier Teytaud. On the Huge Benefit of Decisive Moves in Monte-Carlo Tree Search Algorithms. IEEE Conference on Computational Intelligence and Games, Aug 2010, Copenhagen, Denmark. ⟨inria-00495078⟩
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