  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.
