LiRA: Light-Robust Adversary for Model-based Reinforcement Learning

Published: 09 Apr 2024, Last Modified: 23 Apr 2024ICRA 2024: Back to the FutureEveryoneRevisionsBibTeXCC BY 4.0
Keywords: Reinforcement learning, Adversarial learning, Variational inference, Light robustness
TL;DR: This paper proposes a moderately-robust adversarial learning methodology
Abstract: This study addresses a new adversarial learning framework to make reinforcement learning robust moderately and not conservative too much. To this end, the adversarial learning is first rederived with variational inference. In addition, $\textit{light robustness}$, which allows for maximizing robustness within an acceptable performance degradation, is utilized as a constraint. As a result, the proposed framework, so-called LiRA, can automatically adjust adversary level, balancing robustness and conservativeness. The behaviors of LiRA are confirmed in numerical simulations.
Submission Number: 15