Mountain Car
Benchmarks
| Task Name | Dataset Name | SOTA Result | Trend | |
|---|---|---|---|---|
| Continuous Control | Mountain Car POMDP | Mean Performance26.96 | 30 | |
| Mountain Car | Mountain Car | Mean Return29.97 | 20 | |
| Control | Mountain Car | Robustness Gap0.15 | 12 | |
| Transition model estimation | Mountain Car discretized n = 10^6 | Failure Count0 | 8 | |
| MCTS Aggregation Strategy Evaluation | Mountain Car | MRR1 | 6 | |
| Mountain Car | Mountain Car held-out domains random mountain heights (test) | Avg. Failure Rate0 | 6 | |
| Reinforcement Learning | Mountain Car | Return91.3 | 5 | |
| Mountain Car | Mountain Car | Objective Value116.7 | 5 | |
| Reinforcement Learning | Mountain Car v0 | Steps to Goal98.3 | 5 | |
| Safe Reinforcement Learning | mountain-car Static dynamics | Mean Shield Invocations per Episode0 | 3 | |
| Reinforcement Learning | Mountain Car standard (test) | Episode Length4 | 2 | |
| Optimal Control | Mountain Car | Final Cost34.63 | 2 | |
| End-to-end learning and planning | Mountain Car | Cost (Best)8.57 | 1 |
Showing 13 of 13 rows