Abstracting Imperfect Information Away from Two-Player Zero-Sum Games
- URL: http://arxiv.org/abs/2301.09159v3
- Date: Mon, 31 Jul 2023 21:08:56 GMT
- Title: Abstracting Imperfect Information Away from Two-Player Zero-Sum Games
- Authors: Samuel Sokota, Ryan D'Orazio, Chun Kai Ling, David J. Wu, J. Zico
Kolter, Noam Brown
- Abstract summary: 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 work shows that certain regularized equilibria do not possess the aforementioned non-correspondence problem.
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.
- Score: 85.27865680662973
- License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
- 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.
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