Baohe Zhang

Revisiting Safe Exploration in Safe Reinforcement learning

2024 · arXiv (Cornell University)

Safe reinforcement learning (SafeRL) extends standard reinforcement learning with the idea of safety, where safety is typically defined through the constraint of the expected cost return of a trajectory being below a set limit. However, …