Ryota Tomioka

Regularized Policies are Reward Robust

2021 · arXiv (Cornell University)

Entropic regularization of policies in Reinforcement Learning (RL) is a commonly used heuristic to ensure that the learned policy explores the state-space sufficiently before overfitting to a local optimal policy. The primary motivation for using …