Imagining Trajectories for Anomaly Detection in Reinforcement Learning from Images
ITRM is proposed, a novel approach to anomaly detection in visual reinforcement learning that is fully agent-agnostic and does not require access to policy internals, based on the observation that deviations from nominal environment dynamics can be identified through discrepancies in the latent representations of a lea...