readme: ---
  tags:
  - sac
  - deep-reinforcement-learning
  - reinforcement-learning
  - teach-my-agent-parkour
  model-index:
  - name: ALP-GMM_SAC_bipedal_s2
    results:
    - metrics:
      - type: mean_reward
        value: 222.77 +/- 137.37
        name: mean_reward
      task:
        type: reinforcement-learning
        name: reinforcement-learning
      dataset:
        name: teach-my-agent-parkour
        type: teach-my-agent-parkour
  ---
  
    # Deep RL Agent Playing TeachMyAgent's parkour.
    You can find more info about TeachMyAgent [here](https://developmentalsystems.org/TeachMyAgent/).
    
    Results of our benchmark can be found in our [paper](https://arxiv.org/pdf/2103.09815.pdf).
    
    You can test this policy [here](https://huggingface.co/spaces/flowers-team/Interactive_DeepRL_Demo)
    
    ## Results
    Percentage of mastered tasks (i.e. reward >= 230) after 20 millions steps on the Parkour track. 
    
    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. 
    
    We highlight the best results in bold.
    
    | Algorithm     | BipedalWalker  | Fish          | Climber      | Overall       |
    |---------------|----------------|---------------|--------------|---------------|
    | Random        | 27.25 (± 10.7) | 23.6 (± 21.3) | 0.0 (± 0.0)  | 16.9 (± 18.3) |
    | ADR           | 14.7 (± 19.4)  | 5.3 (± 20.6)  | 0.0 (± 0.0)  | 6.7 (± 17.4)  |
    | ALP-GMM       | **42.7** (± 11.2)  | 36.1 (± 28.5) | 0.4 (± 1.2)  | **26.4** (± 25.7) |
    | Covar-GMM     | 35.7 (± 15.9)  | 29.9 (± 27.9) | 0.5 (± 1.9)  | 22.1 (± 24.2) |
    | GoalGAN       | 25.4 (± 24.7)  | 34.7 ± 37.0)  | 0.8 (± 2.7)  | 20.3 (± 29.5) |
    | RIAC          | 31.2 (± 8.2)   | **37.4** (± 25.4) | 0.4  (± 1.4) | 23.0 (± 22.4) |
    | SPDL          | 30.6 (± 22.8)  | 9.0 (± 24.2)  | **1.0** (± 3.4)  | 13.5 (± 23.0) |
    | Setter-Solver | 28.75 (± 20.7) | 5.1 (± 7.6)   | 0.0 (± 0.0)  | 11.3 (± 17.9) |
  
    # Hyperparameters
    ```python
    {'student': 'SAC'
  'environment': 'parkour'
  'training_steps': 20000000
  'n_evaluation_tasks': 100
  'teacher': 'ALP-GMM'
  'morphology': 'old_classic_bipedal'}
    ```
    