Fighting-Game Gameplay Generation Using Highlight Cues

摘要

In this article, we propose a fighting-game artificial intelligence (AI) that selects its actions from the perspective of highlight generation using Monte Carlo tree search with three highlight cues in the evaluation function. The intended use of this proposed AI is to generate gameplay in live streaming platforms such as Twitch and YouTube where a large number of spectators watch gameplay to entertain themselves. A gameplay analysis and user study are conducted using FightingICE, a fighting-game platform in an international fighting-game AI competition. Results show that gameplay generated by two AI players of the proposed method has more promising characteristics than not only gameplay generated according to an existing method but also gameplay by the top two AI players in the 2019 competition and that it is more entertaining than the latter gameplay.