---
tags:
- sac
- deep-reinforcement-learning
- reinforcement-learning
- teach-my-agent-parkour
model-index:
- name: ALP-GMM_SAC_chimpanzee_s26
  results:
  - metrics:
    - type: mean_reward
      value: -37.97 +/- 106.86
      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).
  
  ## 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': 'climbing_profile_chimpanzee'}
  ```