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Pruning playouts in Monte-Carlo Tree Search for the game of Havannah

Abstract : Monte-Carlo Tree Search (MCTS) is a popular technique for playing multi-player games. In this paper, we propose a new method to bias the playout policy of MCTS. The idea is to prune the decisions which seem " bad " (according to the previous iterations of the algorithm) before computing each playout. Thus, the method evaluates the estimated " good " moves more precisely. We have tested our improvement for the game of Havannah and compared it to several classic improvements. Our method outperforms the classic version of MCTS (with the RAVE improvement) and the different playout policies of MCTS that we have experimented.
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https://hal.archives-ouvertes.fr/hal-01342347
Contributor : Julien Dehos <>
Submitted on : Tuesday, July 5, 2016 - 6:15:29 PM
Last modification on : Tuesday, January 5, 2021 - 1:04:02 PM

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  • HAL Id : hal-01342347, version 1

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Joris Duguépéroux, Ahmad Mazyad, Fabien Teytaud, Julien Dehos. Pruning playouts in Monte-Carlo Tree Search for the game of Havannah. The 9th International Conference on Computers and Games (CG2016), Jun 2016, Leiden, Netherlands. ⟨hal-01342347⟩

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