---
tags:
- MountainCarContinuous-v0
- a2c
- a2c-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. Trainig and usage details are in the 
`2.1 A2C_on_MountainCarContinuous-v0_frameskip.ipynb` jupyter notebook file.

Training progress:
![training progress](screen.jpg)

For some reason agent video demo does not show on the model card, so here's a gif:
![replay](replay.gif)