2024
Enhancing Robustness in Deep Reinforcement Learning: A Lyapunov Exponent Approach
NeurIPS 2024poster
Deep reinforcement learning agents achieve state-of-the-art performance in a wide range of simulated control tasks. However, successful applications to real-world problems remain limited. One reason for this dichotomy is because the learnt policies are not robust to observation noise or adversarial…