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Towards Robust Policy: Enhancing Offline Reinforcement Learning with
  Adversarial Attacks and Defenses

Towards Robust Policy: Enhancing Offline Reinforcement Learning with Adversarial Attacks and Defenses

18 May 2024
Thanh Nguyen
T. Luu
Tri Ton
Chang D. Yoo
    OffRL
    AAML
ArXivPDFHTML

Papers citing "Towards Robust Policy: Enhancing Offline Reinforcement Learning with Adversarial Attacks and Defenses"

4 / 4 papers shown
Title
Offline Reinforcement Learning with Implicit Q-Learning
Offline Reinforcement Learning with Implicit Q-Learning
Ilya Kostrikov
Ashvin Nair
Sergey Levine
OffRL
198
627
0
12 Oct 2021
Uncertainty-Based Offline Reinforcement Learning with Diversified
  Q-Ensemble
Uncertainty-Based Offline Reinforcement Learning with Diversified Q-Ensemble
Gaon An
Seungyong Moon
Jang-Hyun Kim
Hyun Oh Song
OffRL
90
261
0
04 Oct 2021
Robust Reinforcement Learning on State Observations with Learned Optimal
  Adversary
Robust Reinforcement Learning on State Observations with Learned Optimal Adversary
Huan Zhang
Hongge Chen
Duane S. Boning
Cho-Jui Hsieh
50
161
0
21 Jan 2021
Offline Reinforcement Learning: Tutorial, Review, and Perspectives on
  Open Problems
Offline Reinforcement Learning: Tutorial, Review, and Perspectives on Open Problems
Sergey Levine
Aviral Kumar
George Tucker
Justin Fu
OffRL
GP
321
1,662
0
04 May 2020
1