Monte Carlo tree search (MCTS) is being effectively used in many domains, but acquiring good results from building larger trees takes time that can in many cases be impractical. In this article, we show that parallelizing the tree building process using multiple independent trees (root parallelization) can improve results when limited time is available, and compare these results to other parallelization techniques and to results obtained from running for an extended time. We obtained our results using MCTS in the domain of computer Go, which has the most mature implementations. Compared to previous studies, our results are more precise and statistically significant.

中文翻译：

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更多的树或更大的树：并行化蒙特卡罗树搜索

蒙特卡洛树搜索 (MCTS) 正在许多领域中得到有效使用，但是从构建更大的树中获得好的结果需要时间，这在许多情况下是不切实际的。在本文中，我们展示了使用多个独立树并行化树构建过程（根并行化）可以在有限时间可用时改进结果，并将这些结果与其他并行化技术以及长时间运行获得的结果进行比较。我们在计算机围棋领域使用 MCTS 获得了我们的结果，这是最成熟的实现。与之前的研究相比，我们的结果更精确且具有统计学意义。