Deduction of fighting-game countermeasures using the k-nearest neighbor algorithm and a game simulator
Kaito Yamamoto, Syunsuke Mizuno, Chun Yin Chu, Ruck Thawonmas · 2014
This paper proposes an artificial intelligence algorithm that uses the k-nearest neighbor algorithm to predict its opponent's attack action and a game simulator to deduce a countermeasure action for controlling an in-game character in a fighting game. This AI algorithm (AI) aims at achieving good results in the fighting-game AI competition having been organized by our laboratory since 2013. It is also a sample AI, called MizunoAI, publicly available for the 2014 competition at CIG 2014. In fighting games, every action is either advantageous or disadvantageous against another. By predicting its opponent's next action, our AI can devise a countermeasure which is advantageous against that action, leading to higher scores in the game. The effectiveness of the proposed AI is confirmed by the results of matches against the top-three AI entries of the 2013 competition.