Safe Continual Reinforcement Learning in Non-stationary Environments
arXiv:2604.19737v1 Announce Type: new
Abstract: Reinforcement learning (RL) offers a compelling data-driven paradigm for synthesizing controllers for complex systems when accurate physical models are unavailable; however, most existing control-oriente…