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Creating an Upper-Confidence-Tree program for Havannah

Fabien Teytaud 1, 2, 3 Olivier Teytaud 1, 2, 3
1 TANC - Algorithmic number theory for cryptology
Inria Saclay - Ile de France, LIX - Laboratoire d'informatique de l'École polytechnique [Palaiseau]
3 TAO - Machine Learning and Optimisation
CNRS - Centre National de la Recherche Scientifique : UMR8623, Inria Saclay - Ile de France, UP11 - Université Paris-Sud - Paris 11, LRI - Laboratoire de Recherche en Informatique
Abstract : Monte-Carlo Tree Search and Upper Confidence Bounds pro- vided huge improvements in computer-Go. In this paper, we test the generality of the approach by experimenting on another game, Havannah, which is known for being especially difficult for computers. We show that the same results hold, with slight differences related to the absence of clearly known patterns for the game of Havannah, in spite of the fact that Havannah is more related to connection games like Hex than to territory games like Go.
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Submitted on : Saturday, May 2, 2009 - 3:40:09 PM
Last modification on : Thursday, July 8, 2021 - 3:47:53 AM
Long-term archiving on: : Thursday, June 10, 2010 - 8:28:10 PM


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  • HAL Id : inria-00380539, version 1



Fabien Teytaud, Olivier Teytaud. Creating an Upper-Confidence-Tree program for Havannah. ACG 12, May 2009, Pamplona, Spain. ⟨inria-00380539⟩



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