EnsembleCard : A Strategy Ensemble Bot For Two-Player No-Limit Texas Hold’em Poker

Nash Equilibrium is a powerful paradigm to create advanced AI in two-player zero-sum setting, which has a great advantage in getting a statistically significant result. However, playing millions of matches is time-consuming and even more problematic when human player participate in. Single paradigm is hard to hold absolute advantages in this real-world setting because of uncertainty in games. In this paper, we proposed a robust strategy ensemble framework in decision-making tasks, which is useful for real-world settings and has dominant advantage in comparison to single paradigm-based algorithm. We create a strong poker AI with two base decision-makers(including NE searching-base and rule-based), where we improve DeepStack and unlock the potential of CFVnet for creating a high-performance AI. Finally, we applied these approaches to build a poker AI for two-player no-limit Texas Hold’em and won the silver medal of the 2021 Chinese computer poker tournament. And additional experimental results also proved the effectiveness of strategy ensemble framework.