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Erschienen in:
2011 | OriginalPaper | Buchkapitel
Scalability and Parallelization of Monte-Carlo Tree Search
verfasst von : Amine Bourki, Guillaume Chaslot, Matthieu Coulm, Vincent Danjean, Hassen Doghmen, Jean-Baptiste Hoock, Thomas Hérault, Arpad Rimmel, Fabien Teytaud, Olivier Teytaud, Paul Vayssière, Ziqin Yu
Erschienen in: Computers and Games
Verlag: Springer Berlin Heidelberg
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Monte-Carlo Tree Search is now a well established algorithm, in games and beyond. We analyze its scalability, and in particular its limitations and the implications in terms of parallelization. We focus on our Go program
MoGo
and our Havannah program
Shakti
. We use multicore machines and message-passing machines. For both games and on both type of machines we achieve adequate efficiency for the parallel version. However, in spite of promising results in self-play there are situations for which increasing the time per move does not solve anything. Therefore parallelization is not a solution to all our problems. Nonetheless, for problems where the Monte-Carlo part is less biased than in the game of Go, parallelization should be quite efficient, even without shared memory.