Demonstration-Guided Observation Attacks on Black-Box Safe Reinforcement Learning Controllers for Robotic Systems

Safe reinforcement learning (Safe RL) learns robotic controllers that optimize task rewards under safety constraints, yet observation perturbations can induce safety violations. Existing safety-directed attacks often require access to victim networks, gradients, critics, or explicit specifications -