Creating an Upper-Confidence-Tree program for Havannah
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.
Domains
Machine Learning [cs.LG]
Origin : Files produced by the author(s)
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