Stabilizing Neural Control Using Self-Learned Almost Lyapunov Critics
Ya-Chien Chang Sicun Gao Ya-Chien Chang Sicun Gao
The lack of stability guarantee restricts the practical use of learning-based methods in core control problems in robotics. We develop new methods for learning neural control policies and neural Lyapunov critic functions in the modelfree reinforcement learning (RL) setting. We use sample-based approaches and the Almost Lyapunov function conditions to estimate the region of attraction and invarianc...