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--- |
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tags: |
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- sac |
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- deep-reinforcement-learning |
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- reinforcement-learning |
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- teach-my-agent-parkour |
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model-index: |
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- name: ALP-GMM_SAC_fish_s44 |
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results: |
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- metrics: |
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- type: mean_reward |
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value: 268.93 +/- 94.84 |
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name: mean_reward |
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task: |
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type: reinforcement-learning |
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name: reinforcement-learning |
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dataset: |
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name: teach-my-agent-parkour |
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type: teach-my-agent-parkour |
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--- |
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# Deep RL Agent Playing TeachMyAgent's parkour. |
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You can find more info about TeachMyAgent [here](https://developmentalsystems.org/TeachMyAgent/). |
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Results of our benchmark can be found in our [paper](https://arxiv.org/pdf/2103.09815.pdf). |
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You can test this policy [here](https://huggingface.co/spaces/flowers-team/Interactive_DeepRL_Demo) |
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## Results |
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Percentage of mastered tasks (i.e. reward >= 230) after 20 millions steps on the Parkour track. |
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Results shown are averages over 16 seeds along with the standard deviation for each morphology as well as the aggregation of the 48 seeds in the *Overall* column. |
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We highlight the best results in bold. |
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| Algorithm | BipedalWalker | Fish | Climber | Overall | |
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|---------------|----------------|---------------|--------------|---------------| |
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| Random | 27.25 (± 10.7) | 23.6 (± 21.3) | 0.0 (± 0.0) | 16.9 (± 18.3) | |
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| ADR | 14.7 (± 19.4) | 5.3 (± 20.6) | 0.0 (± 0.0) | 6.7 (± 17.4) | |
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| ALP-GMM | **42.7** (± 11.2) | 36.1 (± 28.5) | 0.4 (± 1.2) | **26.4** (± 25.7) | |
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| Covar-GMM | 35.7 (± 15.9) | 29.9 (± 27.9) | 0.5 (± 1.9) | 22.1 (± 24.2) | |
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| GoalGAN | 25.4 (± 24.7) | 34.7 ± 37.0) | 0.8 (± 2.7) | 20.3 (± 29.5) | |
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| RIAC | 31.2 (± 8.2) | **37.4** (± 25.4) | 0.4 (± 1.4) | 23.0 (± 22.4) | |
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| SPDL | 30.6 (± 22.8) | 9.0 (± 24.2) | **1.0** (± 3.4) | 13.5 (± 23.0) | |
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| Setter-Solver | 28.75 (± 20.7) | 5.1 (± 7.6) | 0.0 (± 0.0) | 11.3 (± 17.9) | |
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# Hyperparameters |
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```python |
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{'student': 'SAC' |
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'environment': 'parkour' |
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'training_steps': 20000000 |
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'n_evaluation_tasks': 100 |
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'teacher': 'ALP-GMM' |
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'morphology': 'fish'} |
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``` |
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