Offline Reinforcement Learning on Hopper
2,116.2Average ReturnUWMSG
Evaluation Results
| Method | Links | |
|---|---|---|
| UWMSGAttack Type=Random Dynamics2023.10 | 2,116.2 | |
| UWMSGAttack Type=Random Reward2023.10 | 2,021.1 | |
| MSGAttack Type=Random Reward2023.10 | 1,599.6 | |
| MSGAttack Type=Random Dynamics2023.10 | 1,552.7 | |
| UWMSGAttack Type=Adversarial Dynamics2023.10 | 931.2 | |
| UWMSGAttack Type=Adversarial Reward2023.10 | 751.4 | |
| MSGAttack Type=Adversarial Dynamics2023.10 | 717.7 | |
| MSGAttack Type=Adversarial Reward2023.10 | 651 | |
| SAC-NAttack Type=Random Reward2023.10 | 178.8 | |
| SAC-NAttack Type=Adversarial Reward2023.10 | 111.8 | |
| EDACAttack Type=Random Reward2023.10 | 107.7 | |
| EDACAttack Type=Adversarial Reward2023.10 | 29.2 | |
| EDACAttack Type=Random Dynamics2023.10 | 5.9 | |
| EDACAttack Type=Adversarial Dynamics2023.10 | 5.9 | |
| SAC-NAttack Type=Random Dynamics2023.10 | 3.9 | |
| SAC-NAttack Type=Adversarial Dynamics2023.10 | 3.9 |