AI-controlled characters in fighting games are expected to possess reasonably high skills and behave in a believable, human-like manner, exhibiting a diversity of play styles and strategies. Thus, the development of fighting game AI requires the ability to evaluate these properties. For instance, it should be possible to ensure that the characters created are believable and diverse. In this paper, we show how an automated procedure can be used to compare play styles of individual AI- and human-controlled characters, and to assess human-likeness and diversity of game participants.
@article{arxiv.2108.03599,
title = {Identification of Play Styles in Universal Fighting Engine},
author = {Kaori Yuda and Shota Kamei and Riku Tanji and Ryoya Ito and Ippo Wakana and Maxim Mozgovoy},
journal= {arXiv preprint arXiv:2108.03599},
year = {2021}
}