Structured Parallel Programming for Monte Carlo Tree Search
S. Ali Mirsoleimani, Aske Plaat, Jaap van den Herik, Jos Vermaseren
TL;DR
This paper introduces a novel structured parallel programming approach for Monte Carlo Tree Search using a pipeline pattern, enabling efficient, scalable parallelization with reduced synchronization overhead.
Contribution
It presents the first structured parallel programming framework for MCTS and a lock-free tree data structure to improve scalability and performance.
Findings
3PMCTS scales well to many cores
Reduces synchronization overhead
Outperforms existing parallel MCTS methods
Abstract
In this paper, we present a new algorithm for parallel Monte Carlo tree search (MCTS). It is based on the pipeline pattern and allows flexible management of the control flow of the operations in parallel MCTS. The pipeline pattern provides for the first structured parallel programming approach to MCTS. Moreover, we propose a new lock-free tree data structure for parallel MCTS which removes synchronization overhead. The Pipeline Pattern for Parallel MCTS algorithm (called 3PMCTS), scales very well to higher numbers of cores when compared to the existing methods.
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Taxonomy
TopicsArtificial Intelligence in Games · Algorithms and Data Compression · Parallel Computing and Optimization Techniques