Venue: ICML 2021 Workshop AML

Reviews:

final_score: rating: Accept
review_content: This paper compare the perturbations generated in adversarial training agent and vanilla DRL agent in different frequencies in the Fourier domain. The empirical results shows that the adversarial-training is more vulnerable to low-frequency perturbation in Fourier domain provided by targeted attack.

Main Concerns:
1. need more victim policies and more adversarial-trained policies. I also suggest to test on MuJoCo environments.
2. other kinds of perturbations.  My main concern of this work is whether this conclusions holds for other kinds of perturbations.


review_title: The results are interesting but one-sided

Meta-review: This paper studied adversarial attacks on deep RL policies. There are some concerns raised by the reviewers, which could be addressed in the revision.
Decision: Accept (Poster)