2024
Safe Reinforcement Learning via Hierarchical Adaptive Chance-Constraint Safeguards
IROS 2024poster
Ensuring safety in Reinforcement Learning (RL), typically framed as a Constrained Markov Decision Process (CMDP), is crucial for real-world exploration applications. Current approaches in handling CMDP struggle to balance optimality and feasibility, as direct optimization methods can-not ensure stat…