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Exploiting Game Decompositions in Monte Carlo Tree Search

Abstract : In this paper, we propose a variation of the MCTS framework to perform a search in several trees to exploit game decompositions. Our Multiple Tree MCTS (MT-MCTS) approach builds simultaneously multiple MCTS trees corresponding to the different sub-games and allows , like MCTS algorithms, to evaluate moves while playing. We apply MT-MCTS on decomposed games in the General Game Playing framework. We present encouraging results on single player games showing that this approach is promising and opens new avenues for further research in the domain of decomposition exploitation. Complex compound games are solved from 2 times faster (Incredible) up to 25 times faster (Nonogram).
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Contributor : Jean-Noël Vittaut Connect in order to contact the contributor
Submitted on : Friday, December 11, 2020 - 8:37:17 PM
Last modification on : Sunday, June 26, 2022 - 3:00:46 AM


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  • HAL Id : hal-02317329, version 2


Aline Hufschmitt, Jean-Noël Vittaut, Nicolas Jouandeau. Exploiting Game Decompositions in Monte Carlo Tree Search. 16th Advances in Computer Games Conference, Aug 2019, Macao, China. ⟨hal-02317329v2⟩



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