Solving Large Imperfect Information Games Using CFR+

Understand

Counterfactual Regret Minimization and variants (e.g.

• Public Chance Sampling CFR and Pure CFR) have been known as the best approaches for creating approximate Nash equilibrium solutions for imperfect information games such as poker.
• This paper introduces CFR$^+$, a new algorithm that typically outperforms the previously known algorithms by an order of magnitude or more in terms of computation time while also potentially requiring less memory.