Yikun Cheng

Improving the Robustness of Reinforcement Learning Policies with $\mathcal{L}_{1}$ Adaptive Control

2021 · arXiv (Cornell University)

A reinforcement learning (RL) control policy could fail in a new/perturbed environment that is different from the training environment, due to the presence of dynamic variations. For controlling systems with continuous state and action spaces, …