Minimizing Weighted Counterfactual Regret with Optimistic Online Mirror
Descent
Minimizing Weighted Counterfactual Regret with Optimistic Online Mirror
Descent
Counterfactual regret minimization (CFR) is a family of algorithms for effectively solving imperfect-information games. It decomposes the total regret into counterfactual regrets, utilizing local regret minimization algorithms, such as Regret Matching (RM) or RM+, to minimize them. Recent research establishes a connection between Online Mirror Descent (OMD) and RM+, paving …