Computer Science > Computer Science and Game Theory
[Submitted on 24 Mar 2024 (v1), last revised 3 Apr 2024 (this version, v2)]
Title:A Coupled Optimization Framework for Correlated Equilibria in Normal-Form Game
View PDF HTML (experimental)Abstract:In competitive multi-player interactions, simultaneous optimality is a key requirement for establishing strategic equilibria. This property is explicit when the game-theoretic equilibrium is the simultaneously optimal solution of coupled optimization problems. However, no such optimization problems exist for the correlated equilibrium, a strategic equilibrium where the players can correlate their actions. We address the lack of a coupled optimization framework for the correlated equilibrium by introducing an {unnormalized game} -- an extension of normal-form games in which the player strategies are lifted to unnormalized measures over the joint actions. We show that the set of fully mixed generalized Nash equilibria of this unnormalized game is a subset of the correlated equilibrium of the normal-form game. Furthermore, we introduce an entropy regularization to the unnormalized game and prove that the entropy-regularized generalized Nash equilibrium is a sub-optimal correlated equilibrium of the normal form game where the degree of sub-optimality depends on the magnitude of regularization. We prove that the entropy-regularized unnormalized game has a closed-form solution, and empirically verify its computational efficacy at approximating the correlated equilibrium of normal-form games.
Submission history
From: Sarah Li Ms. [view email][v1] Sun, 24 Mar 2024 16:33:01 UTC (1,111 KB)
[v2] Wed, 3 Apr 2024 09:10:47 UTC (1,111 KB)
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