Paper

Robust Deep Reinforcement Learning against Adversarial Perturbations on State Observations

A deep reinforcement learning (DRL) agent observes its states through observations, which may contain natural measurement errors or adversarial noises. Since the observations deviate from the true states, they can mislead the agent into making suboptimal actions... (read more)

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