Compact CFR

Eric Griffin Jackson

Abstract: This paper describes a collection of ideas that allow large games of imperfect information to be solved with counterfactual regret minimization (CFR) using little memory. We replace the regret matching component of CFR with a simple approach known as "follow-the-leader." This helps us quantize the regret values computed in CFR to a single byte. We also investigate not maintaining the accumulated strategy, which saves additional memory. Ultimately, our collection of techniques allows CFR to be run with only 1/16 of the memory required by classic approaches. We present experimental results on poker.