AI RESEARCH
Real-Time Parallel Counterfactual Regret Minimization
arXiv CS.AI
•
ArXi:2605.19928v1 Announce Type: cross Counterfactual Regret Minimization (CFR) is the dominant algorithmic family for solving large imperfect-information games, underpinning breakthroughs such as Libratus and Pluribus in No-Limit Texas Hold'em poker. In real-time game-playing systems, the solver must compute a near-equilibrium strategy within a strict time budget of only a few seconds per decision, and the number of CFR iterations completed in this window directly determines play strength.