2022
Enhancing Safe Exploration Using Safety State Augmentation
NeurIPS 2022accept
Safe exploration is a challenging and important problem in model-free reinforcement learning (RL). Often the safety cost is sparse and unknown, which unavoidably leads to constraint violations - a phenomenon ideally to be avoided in safety-critical applications. We tackle this problem by augmenting…