Polynomial-time Computation of Exact Correlated Equilibrium in Compact Games
Albert Xin Jiang, Kevin Leyton-Brown

TL;DR
This paper presents a polynomial-time algorithm for computing exact correlated equilibria in compact games, improving upon previous methods by addressing numerical issues and producing simpler, polynomial-sized support distributions.
Contribution
It introduces a modified Ellipsoid Against Hope algorithm with a new separation oracle that guarantees exact correlated equilibrium computation efficiently.
Findings
Algorithm guarantees polynomial-time identification of exact correlated equilibria.
Produces equilibria with polynomial-sized supports, simpler to represent.
Simplifies analysis and avoids numerical precision issues.
Abstract
In a landmark paper, Papadimitriou and Roughgarden described a polynomial-time algorithm ("Ellipsoid Against Hope") for computing sample correlated equilibria of concisely-represented games. Recently, Stein, Parrilo and Ozdaglar showed that this algorithm can fail to find an exact correlated equilibrium, but can be easily modified to efficiently compute approximate correlated equilibria. Currently, it remains unresolved whether the algorithm can be modified to compute an exact correlated equilibrium. We show that it can, presenting a variant of the Ellipsoid Against Hope algorithm that guarantees the polynomial-time identification of exact correlated equilibrium. Our new algorithm differs from the original primarily in its use of a separation oracle that produces cuts corresponding to pure-strategy profiles. As a result, we no longer face the numerical precision issues encountered by…
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Taxonomy
TopicsGame Theory and Applications · Economic theories and models · Game Theory and Voting Systems
