Provided are certified adversarial robustness for deep reinforcement learning. The present disclosure describes systems and methods that include calculating one or more lower bound state-action values based on a corrupted observation and a predetermined perturbation parameter; and selecting an action corresponding to a lower bound state-action value having the highest value.
CERTIFIED ADVERSARIAL ROBUSTNESS FOR DEEP REINFORCEMENT LEARNING