Provably Safe, Yet Scalable Reinforcement Learning

Kai S. Yun, Zeyang Li, Navid Azizan

Safe reinforcement learning (RL) aims to learn policies that optimize rewards while satisfying constraints. Predominant approaches rely on soft-constrained policy optimization, whi…