CFR (Counterfactual Regret Minimization)

Counterfactual Regret Minimization is an algorithm that iteratively solves imperfect-information games like poker. It works by simulating hands, calculating 'regret' for not taking the best action at each decision point, and adjusting future strategies to minimize total regret. Over millions of iterations, CFR converges to a Nash Equilibrium. Variants like CFR+ and Discounted CFR++ speed up convergence significantly.