Evolution Strategies for Approximate Solution of Bayesian Games
Z Li and MP Wellman
35th AAAI Conference on Artificial Intelligence, Feb 2021 (forthcoming).
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…