cheetah
Benchmarks
| Task Name | Dataset Name | SOTA Result | Trend | |
|---|---|---|---|---|
| Reinforcement Learning | Cheetah | Return934.76 | 24 | |
| Reinforcement Learning | Cheetah Task 2 | Return21,100 | 12 | |
| Reinforcement Learning | Cheetah Task 1 | Return15.4 | 12 | |
| Continuous Control | cheetah | Average Reward934.76 | 12 | |
| Actuator Inversion | Cheetah Ceval-in (eval-in) | AER319 | 8 | |
| Actuator Inversion | Cheetah (train) | AER319 | 8 | |
| Contact State Detection | Mini-Cheetah real-world | F1 (Leg LF)93.6 | 6 | |
| Single-life task completion | Cheetah | Average Steps74,300 | 5 | |
| Meta-Reinforcement Learning | Cheetah vel-ood | FLOPs (k)0.53 | 3 | |
| Continuous Control | hardCheetah | Average Reward1.311 | 3 | |
| Latent space prediction | Cheetah | MSE0.0003 | 2 | |
| Reinforcement Learning | Cheetah | Zero-shot Reward10,941,130 | 1 |
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