English

Abstracting Imperfect Information Away from Two-Player Zero-Sum Games

Computer Science and Game Theory 2023-08-02 v3 Artificial Intelligence Machine Learning

Abstract

In their seminal work, Nayyar et al. (2013) showed that imperfect information can be abstracted away from common-payoff games by having players publicly announce their policies as they play. This insight underpins sound solvers and decision-time planning algorithms for common-payoff games. Unfortunately, a naive application of the same insight to two-player zero-sum games fails because Nash equilibria of the game with public policy announcements may not correspond to Nash equilibria of the original game. As a consequence, existing sound decision-time planning algorithms require complicated additional mechanisms that have unappealing properties. The main contribution of this work is showing that certain regularized equilibria do not possess the aforementioned non-correspondence problem -- thus, computing them can be treated as perfect-information problems. Because these regularized equilibria can be made arbitrarily close to Nash equilibria, our result opens the door to a new perspective to solving two-player zero-sum games and yields a simplified framework for decision-time planning in two-player zero-sum games, void of the unappealing properties that plague existing decision-time planning approaches.

Keywords

Cite

@article{arxiv.2301.09159,
  title  = {Abstracting Imperfect Information Away from Two-Player Zero-Sum Games},
  author = {Samuel Sokota and Ryan D'Orazio and Chun Kai Ling and David J. Wu and J. Zico Kolter and Noam Brown},
  journal= {arXiv preprint arXiv:2301.09159},
  year   = {2023}
}
R2 v1 2026-06-28T08:17:22.089Z