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Towards a solution of 7x7 Go with Meta-MCTS

Abstract : Solving board games is a hard task, in particular for games in which classical tools like alpha-beta and proof-number-search are some- how weak. In particular, Go is not solved (in any sense of solving, even the weakest) beyond 6x6. We here investigate the use of Meta-Monte- Carlo-Tree-Search, for building a huge 7x7 opening book. In particular, we report the twenty wins (out of twenty games) that were obtained re- cently in 7x7 Go against pros; we also show that in one of the games, with no human error, the pro might have won.
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https://hal.inria.fr/hal-01077624
Contributor : Olivier Teytaud <>
Submitted on : Sunday, October 26, 2014 - 1:45:00 AM
Last modification on : Thursday, June 17, 2021 - 3:48:01 AM

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  • HAL Id : hal-01077624, version 1

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Cheng-Wei Chou, Li-Wen Wu, Hui-Min Wang, Fabien Teytaud, Olivier Teytaud, et al.. Towards a solution of 7x7 Go with Meta-MCTS. Advances in Computer Games, 2011, Tilburg, Netherlands. pp.12. ⟨hal-01077624⟩

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