Modiﬁcation of UCT with Patterns in Monte-Carlo Go

Sylvain Gelly; Yizao Wang; Rémi Munos; Olivier Teytaud

inria-00117266, version 2

Modiﬁcation of UCT with Patterns in Monte-Carlo Go

Sylvain Gelly () ¹, Yizao Wang ^1, 2, Rémi Munos ^2, 3, Olivier Teytaud ¹

N° RR-6062 (2006)

Abstract: Algorithm UCB1 for multi-armed bandit problem has already been extended to Algorithm UCT (Upper bound Confidence for Tree) which works for minimax tree search. We have developed a Monte-Carlo Go program, MoGo, which is the first computer Go program using UCT. We explain our modification of UCT for Go application and also the intelligent random simulation with patterns which has improved significantly the performance of MoGo. UCT combined with pruning techniques for large Go board is discussed, as well as parallelization of UCT. MoGo is now a top level Go program on $9\times9$ and $13\times13$ Go boards.

1: TAO (INRIA Futurs)
INRIA – CNRS : UMR8623 – Université Paris XI - Paris Sud
2: Centre de Mathématiques Appliquées (CMAP)
CNRS : UMR7641 – Université de Versailles Saint-Quentin-en-Yvelines – Polytechnique - X
3: SEQUEL (INRIA Futurs)
INRIA – CNRS : UMR8146 – Université Lille I - Sciences et technologies – Université Lille III - Sciences humaines et sociales – Ecole Centrale de Lille

inria-00117266, version 2
http://hal.inria.fr/inria-00117266
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From: Rapport De Recherche Inria <>
Submitted on: Tuesday, 12 December 2006 10:35:11
Updated on: Tuesday, 12 December 2006 10:35:24

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