Bo An

most citedS

^{2}

AC: Energy-Based Reinforcement Learning with Stein Soft Actor Critic

2 citations · 2 across the 1 of their papers we have counts for

collaborators

2 papers

cs.LG2025

Policy Regularization on Globally Accessible States in Cross-Dynamics Reinforcement Learning

Zhenghai Xue, Lang Feng, Jiacheng Xu +4

To learn from data collected in diverse dynamics, Imitation from Observation (IfO) methods leverage expert state trajectories based on the premise that recovering expert state dist…

cs.LG2024★ 2 cited

S $^{2}$ AC: Energy-Based Reinforcement Learning with Stein Soft Actor Critic

Safa Messaoud, Billel Mokeddem, Zhenghai Xue +4

Learning expressive stochastic policies instead of deterministic ones has been proposed to achieve better stability, sample complexity, and robustness. Notably, in Maximum Entropy…

Policy Regularization on Globally Accessible States in Cross-Dynamics Reinforcement Learning

S2AC: Energy-Based Reinforcement Learning with Stein Soft Actor Critic

S $^{2}$ AC: Energy-Based Reinforcement Learning with Stein Soft Actor Critic