Paul Stahlhofen

Admissable: Training Reinforcement Learning Agents against Adversarial Missingness

In order to make Reinforcement Learning algorithms applicable in real world scenarios, safety must be ensured even under adverse operating conditions. In this work, we consider the challenge of adversarial feature missingness: a scenario in which an adversary occludes features from the agent's observation in order to r...