2026
Revisiting Regularized Policy Optimization for Stable and Efficient Reinforcement Learning in Two-Player Games
ICML 2026poster
Two-player games such as board games have long been used as traditional benchmark for reinforcement learning. This work revisits a regularized policy optimization with reverse Kullback-Leibler divergence and entropy divergence and analyzes this combination on two-player zero-sum settings from theore…