蒙特卡罗树搜索在格斗游戏AI中的应用

2016 IEEE 5th Global Conference on Consumer Electronics Pub Date : 2016-10-01 DOI:10.1109/GCCE.2016.7800536

Shubu Yoshida, M. Ishihara, Taichi Miyazaki, Y. Nakagawa, Tomohiro Harada, R. Thawonmas

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引用次数: 31

摘要

本文描述了蒙特卡罗树搜索(MCTS)在格斗游戏人工智能中的应用。MCTS是一种使用随机模拟的最佳优先搜索技术。在本文中，我们在计算智能与游戏会议上的游戏AI竞赛平台combatingice上评估了它的有效性。我们的结果证实了MCTS是在上述平台上控制游戏AI的有效搜索。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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Application of Monte-Carlo tree search in a fighting game AI

This paper describes an application of Monte-Carlo Tree Search (MCTS) in a fighting game AI. MCTS is a best-first search technique that uses stochastic simulations. In this paper, we evaluate its effectiveness on FightingICE, a game AI competition platform at Computational Intelligence and Games Conferences. Our results confirm that MCTS is an effective search for controlling a game AI in the aforementioned platform.

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2016 IEEE 5th Global Conference on Consumer Electronics

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