Creating an Upper-Confidence-Tree program for Havannah

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Abstract

Monte-Carlo Tree Search and Upper Confidence Bounds provided huge improvements in computer-Go. In this paper, we test the generality of the approach by experimenting on the 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. © 2010 Springer-Verlag Berlin Heidelberg.

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Teytaud, F., & Teytaud, O. (2010). Creating an Upper-Confidence-Tree program for Havannah. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 6048 LNCS, pp. 65–74). https://doi.org/10.1007/978-3-642-12993-3_7

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