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

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.