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Fast swap regret minimization and applications to approximate correlated equilibria

Published 30 Oct 2023 in cs.GT, cs.AI, cs.DS, cs.LG, and cs.MA | (2310.19647v2)

Abstract: We give a simple and computationally efficient algorithm that, for any constant $\varepsilon>0$, obtains εT\varepsilon T-swap regret within only T=polylog(n)T = \mathsf{polylog}(n) rounds; this is an exponential improvement compared to the super-linear number of rounds required by the state-of-the-art algorithm, and resolves the main open problem of [Blum and Mansour 2007]. Our algorithm has an exponential dependence on ε\varepsilon, but we prove a new, matching lower bound. Our algorithm for swap regret implies faster convergence to ε\varepsilon-Correlated Equilibrium (ε\varepsilon-CE) in several regimes: For normal form two-player games with nn actions, it implies the first uncoupled dynamics that converges to the set of ε\varepsilon-CE in polylogarithmic rounds; a polylog(n)\mathsf{polylog}(n)-bit communication protocol for ε\varepsilon-CE in two-player games (resolving an open problem mentioned by [Babichenko-Rubinstein'2017, Goos-Rubinstein'2018, Ganor-CS'2018]); and an O~(n)\tilde{O}(n)-query algorithm for ε\varepsilon-CE (resolving an open problem of [Babichenko'2020] and obtaining the first separation between ε\varepsilon-CE and ε\varepsilon-Nash equilibrium in the query complexity model). For extensive-form games, our algorithm implies a PTAS for normal\mathit{normal} form\mathit{form} correlated\mathit{correlated} equilibria\mathit{equilibria}, a solution concept often conjectured to be computationally intractable (e.g. [Stengel-Forges'08, Fujii'23]).

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