Trajectory Entropy Reinforcement Learning for Robust Robot Motor Skill Learning
This work introduces a novel inductive bias towards simple policies in reinforcement learning by minimizing the entropy of entire action trajectories, corresponding to the number of bits required to describe information in action trajectories after the agent observes state trajectories.
Bang You, Chenxu Wang, Wen-Ju Yang et al.
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