Francesco-A/ppo-MountainCar-v0

PPO Agent playing MountainCar-v0

This is a trained model of a PPO agent playing MountainCar-v0 using the stable-baselines3 library.

Model Details

• Model Name: ppo-MountainCar-v0
• Model Type: Proximal Policy Optimization (PPO)
• Policy Architecture: MultiLayerPerceptron (MLPPolicy)
• Environment: MountainCar-v0
• Training Data: The model was trained using three consecutive training sessions:
  • First training session: Total timesteps = 1,000,000
  • Second training session: Total timesteps = 500,000
  • Third training session: Total timesteps = 500,000

Model Parameters

- n_steps: 2048
- batch_size: 64
- n_epochs: 8
- gamma: 0.999
- gae_lambda: 0.95
- ent_coef: 0.01
- max_grad_norm: 0.5
- Verbose: Enabled (Verbose level = 1)