Evolution Strategies for Approximate Solution of Bayesian Games

Z Li and MP Wellman 35th AAAI Conference on Artificial Intelligence, pages 5531-5540, Feb 2021. Abstract We address the problem of solving complex Bayesian games, characterized by high-dimensional type and action spaces, many (> 2) players,…

Structure learning for approximate solution of many-player games

Z Li and MP Wellman 34th AAAI Conference on Artificial Intelligence, pages 2119-2127, Feb 2020. Abstract Games with many players are difficult to solve or even specify without adopting structural assumptions that enable representation in…

Bounding regret in empirical games

S Jecmen, A Sinha, Z Li, L Tran-Thanh 34th AAAI Conference on Artificial Intelligence (AAAI), 2020. Abstract Empirical game-theoretic analysis refers to a set of models and techniques for solving large-scale games. However, there is a lack…