Shubu Yoshida, M. Ishihara, Taichi Miyazaki, Y. Nakagawa, Tomohiro Harada, R. Thawonmas
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引用次数: 31
Abstract
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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