no code implementations • 10 Sep 2022 • Hanping Zhang, Yuhong Guo
As safety violations can lead to severe consequences in real-world robotic applications, the increasing deployment of Reinforcement Learning (RL) in robotic domains has propelled the study of safe exploration for reinforcement learning (safe RL).
no code implementations • 29 Jun 2021 • Hanping Zhang, Yuhong Guo
In this work, we propose a novel policy-aware adversarial data augmentation method to augment the standard policy learning method with automatically generated trajectory data.