Student of Games: A unified learning algorithm for both perfect and imperfect information games.

ABSTRACT: Games have a long history as benchmarks for progress in artificial intelligence. Approaches using search and learning produced strong performance across many perfect information games, and approaches using game-theoretic reasoning and learning demonstrated strong performance for specific imperfect information poker variants. We introduce Student of Games, a general-purpose algorithm that unifies previous approaches, combining guided search, self-play learning, and game-theoretic reasoning. Student of Games achieves strong empirical performance in large perfect and imperfect information games-an important step toward truly general algorithms for arbitrary environments. We prove that Student of Games is sound, converging to perfect play as available computation and approximation capacity inc

SUBMITTER: Schmid M 

PROVIDER: S-EPMC10651118 | biostudies-literature | 2023 Nov

REPOSITORIES: biostudies-literature