Playstyle Generation for Geister With Genetic Algorithm and Clustering
Keisuke Tomoda, Koji Hasebe
2023
Abstract
Studies on game-playing agents have made various attempts to develop agents with characteristic playstyle. Most of these studies either generated agents with predetermined playstyles or simultaneously generated different playstyles without defining a specific playstyle for single-player complete information games. However, the generation of agents with different playstyles for multi-player imperfect information games has not been thoroughly investigated. Therefore, in this study, we have proposed an automatic playstyle generation method for a two-player imperfect information game called Geister. The basic idea is to use a genetic algorithm to optimize agents whose genes represent parameters that determine the manner of guessing hidden information. By clustering the genes with high fitness, obtained using this process, agents with different playstyles are generated simultaneously. From the results of the experiments, our proposed method generated five different playstyles with cyclic dominance relationships.
DownloadPaper Citation
in Harvard Style
Tomoda K. and Hasebe K. (2023). Playstyle Generation for Geister With Genetic Algorithm and Clustering. In Proceedings of the 15th International Conference on Agents and Artificial Intelligence - Volume 3: ICAART, ISBN 978-989-758-623-1, pages 916-922. DOI: 10.5220/0011801400003393
in Bibtex Style
@conference{icaart23,
author={Keisuke Tomoda and Koji Hasebe},
title={Playstyle Generation for Geister With Genetic Algorithm and Clustering},
booktitle={Proceedings of the 15th International Conference on Agents and Artificial Intelligence - Volume 3: ICAART,},
year={2023},
pages={916-922},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0011801400003393},
isbn={978-989-758-623-1},
}
in EndNote Style
TY - CONF
JO - Proceedings of the 15th International Conference on Agents and Artificial Intelligence - Volume 3: ICAART,
TI - Playstyle Generation for Geister With Genetic Algorithm and Clustering
SN - 978-989-758-623-1
AU - Tomoda K.
AU - Hasebe K.
PY - 2023
SP - 916
EP - 922
DO - 10.5220/0011801400003393