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Published in:
2011 | OriginalPaper | Chapter
Biasing Monte-Carlo Simulations through RAVE Values
Authors : Arpad Rimmel, Fabien Teytaud, Olivier Teytaud
Published in: Computers and Games
Publisher: Springer Berlin Heidelberg
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The Monte-Carlo Tree Search algorithm has been successfully applied in various domains. However, its performance heavily depends on the Monte-Carlo part. In this paper, we propose a generic way of improving the Monte-Carlo simulations by using RAVE values, which already strongly improved the tree part of the algorithm. We prove the generality and efficiency of our approach by showing improvements on two different applications: the game of Havannah and the game of Go.