readme: ---
  tags:
  - MountainCarContinuous-v0
  - a2c
  - reinforcement-learning
  - custom-implementation
  model-index:
  - name: A2C-MountainCarContinuous-v0
    results:
    - task:
        type: reinforcement-learning
        name: reinforcement-learning
      dataset:
        name: MountainCarContinuous-v0
        type: MountainCarContinuous-v0
      metrics:
      - type: mean_reward
        value: 90.98 +/- 3.32
        name: mean_reward
        verified: false
  ---
  
  
  # **A2C** Agent playing **MountainCarContinuous-v0**
  
  Custom A2C model with a frameskip that solves the MountainCarContinuous-v0 env. Training and usage details are in the 
  `2.1 A2C_on_MountainCarContinuous-v0_frameskip.ipynb` jupyter notebook file.
  
  Training progress:
  ![training progress](screen.jpg)
  
  In case video demo does not show on the model card, here's a gif:
  ![replay](replay.gif)