Correlation in Extensive-Form Games: Saddle-Point Formulation and Benchmarks

Gabriele Farina, Chun Kai Ling, Fei Fang, Tuomas Sandholm

Neural Information Processing Systems 

While Nash equilibrium in extensive-form games is well understood, very little is known about the properties of extensive-form correlated equilibrium (EFCE), both from a behavioral and from a computational point of view. In this setting, the strategic behavior of players is complemented by an external device that privately recommends moves to agents as the game progresses; players are free to deviate at any time, but will then not receive future recommendations.