| Paper | Code | Meta-test success rate | Meta-train success rate | Meta-test success rate (zero-shot) | ModelName | ReleaseDate |
|---|---|---|---|---|---|---|
| Meta-World: A Benchmark and Evaluation for Multi-Task and Meta Reinforcement Learning | ✓ Link | 36% | 25% | MAML | 2019-10-24 | |
| Meta-World: A Benchmark and Evaluation for Multi-Task and Meta Reinforcement Learning | ✓ Link | 10% | 50% | RL^2 | 2019-10-24 | |
| Analyzing Policy Distillation on Multi-Task Learning and Meta-Reinforcement Learning in Meta-World | 5.4% | DnC | 2020-02-08 | |||
| Meta-World: A Benchmark and Evaluation for Multi-Task and Meta Reinforcement Learning | ✓ Link | 0% | 42.78% | PEARL | 2019-10-24 | |
| Procedural Generalization by Planning with Self-Supervised World Models | 97.8% | 25 | MZ+Recon | 2021-11-02 | ||
| Procedural Generalization by Planning with Self-Supervised World Models | 97.6% | 26.5 | MZ | 2021-11-02 |