Opponent Modeling in Multiplayer Imperfect-Information Games
Abstract
In many real-world settings agents engage in strategic interactions with multiple opposing agents who can employ a wide variety of strategies. The standard approach for designing agents for such settings is to compute or approximate a relevant game-theoretic solution concept such as Nash equilibrium and then follow the prescribed strategy. However, such a strategy ignores any observations of opponents' play, which may indicate shortcomings that can be exploited. We present an approach for opponent modeling in multiplayer imperfect-information games where we collect observations of opponents' play through repeated interactions. We run experiments against a wide variety of real opponents and exact Nash equilibrium strategies in three-player Kuhn poker and show that our algorithm significantly outperforms all of the agents, including the exact Nash equilibrium strategies.
Cite
@article{arxiv.2212.06027,
title = {Opponent Modeling in Multiplayer Imperfect-Information Games},
author = {Sam Ganzfried and Kevin A. Wang and Max Chiswick},
journal= {arXiv preprint arXiv:2212.06027},
year = {2024}
}