Published in (*To Appear*) IEEE International Conference on Robotics and Automation (ICRA), 2021
We introduce Conditioning for Action Policy Smoothness (CAPS), an effective yet intuitive regularization on action policies, which offers consistent improvement in the smoothness of the learned state-to-action mappings of neural network controllers, reflected in the elimination of high-frequency components in the control signal.
Recommended citation: Mysore, S., Mabsout, B., Mancuso, R., & Saenko, K. (2021). "Regularizing Action Policies for Smooth Control with Reinforcement Learning", IEEE International Conference on Robotics and Automation 2021, Xian, China. https://arxiv.org/abs/2012.06644