A Unified View of Large-scale Zero-sum Equilibrium Computation

Understand

The task of computing approximate Nash equilibria in large zero-sum extensive-form games has received a tremendous amount of attention due mainly to the Annual Computer Poker Competition.

• Immediately after its inception, two competing and seemingly different approaches emerged---one an application of no-regret online learning, the other a sophisticated gradient method applied to a convex-concave saddle-point formulation.
• Since then, both approaches have grown in relative isolation with advancements on one side not effecting the other.
• In this paper, we rectify this by dissecting and, in a sense, unify the two views.