Abstract
Recently, with the rapid development of artificial intelligence technology, there are growing researchers drawing their attention on the field of computer game. In two-player zero-sum extensive games with imperfect information, counterfactual regret (CFR) method is one of the most popular method to solve Nash equilibrium strategy. Therefore, we have carried on a wide range of research and analysis on the CFR and its related improved methods in recent years. In this paper, we firstly introduce the process of solving the strategy of Nash equilibrium based on CFR method. Then, some related improved methods of CFR are reviewed. The bare extended experiments are carried out to help researchers to understand these methods more conveniently. Further, some successful applications and common test platforms are described. Finally, the paper is ended with a conclusion of CFR-based methods and a prediction of future development.
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