
  # 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': 'Self-Paced'
'morphology': 'climbing_profile_chimpanzee'}
  ```
  
{"tags": ["sac", "deep-reinforcement-learning", "reinforcement-learning", "teach-my-agent-parkour"], "model-index": [{"name": "Self-Paced_SAC_chimpanzee_s1", "results": [{"task": {"type": "reinforcement-learning", "name": "reinforcement-learning"}, "dataset": {"name": "teach-my-agent-parkour", "type": "teach-my-agent-parkour"}, "metrics": [{"type": "mean_reward", "value": "49.61 +/- 117.61", "name": "mean_reward"}]}]}]}
sac deep-reinforcement-learning reinforcement-learning teach-my-agent-parkour arxiv:2103.09815 model-index region:us
TAGS
#sac #deep-reinforcement-learning #reinforcement-learning #teach-my-agent-parkour #arxiv-2103.09815 #model-index #region-us 

Deep RL Agent Playing TeachMyAgent's parkour.
=============================================


You can find more info about TeachMyAgent here.


Results of our benchmark can be found in our paper.


You can test this policy here


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.



Hyperparameters
===============



TAGS
#sac #deep-reinforcement-learning #reinforcement-learning #teach-my-agent-parkour #arxiv-2103.09815 #model-index #region-us 

passage: TAGS
#sac #deep-reinforcement-learning #reinforcement-learning #teach-my-agent-parkour #arxiv-2103.09815 #model-index #region-us 
