Jonathan Chong

Region-Driven Adaptation for Constrained Reinforcement Learning-Based Control

This paper presents a region-driven adaptation for constrained reinforcement learning (RL)-based control for systems with unknown nonlinear dynamics. For safety-critical control, several noteworthy results have been presented that ensure safety through the control barrier function (CBF) theory. One