Jeffrey Huang

Trade-Off Between Robustness and Rewards Adversarial Training for Deep Reinforcement Learning Under Large Perturbations

Deep Reinforcement Learning (DRL) has become a popular approach for training robots due to its generalization promise, complex task capacity and minimal human intervention. Nevertheless, DRL-trained controllers are vulnerable to even the smallest of perturbations on its inputs which can lead to cata