Safety Correction from Baseline: Towards the Risk-aware Policy in Robotics via Dual-agent Reinforcement Learning
Linrui Zhang,Zichen Yan,Li Shen,Shoujie Li,Xueqian Wang,Dacheng Tao,Linrui Zhang,Zichen Yan,Li Shen,Shoujie Li,Xueqian Wang,Dacheng Tao
Learning a risk-aware policy is essential but rather challenging in unstructured robotic tasks. Safe reinforcement learning methods open up new possibilities to tackle this problem. However, the conservative policy updates make it intractable to achieve sufficient exploration and desirable performance in complex, sample-expensive environments. In this paper, we propose a dual-agent safe reinforcem...
