Advancing Out-of-Distribution Detection Methods for Reinforcement Learning: Addressing Temporally Correlated Anomalies

This paper proposes novel benchmark environments and a new detection method called DEXTER to address the challenge of identifying temporally correlated anomalies in reinforcement learning environments, which current state-of-the-art detectors struggle to identify.