On the Parallelization of Monte-Carlo planning
Abstract
We provide a parallelization with and without shared-memory for Bandit-Based Monte-Carlo Planning algorithms, applied to the game of Go. The resulting algorithm won the first non-blitz game against a professionnal human player in 9x9 Go.
Origin : Files produced by the author(s)
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