|
--- |
|
tags: |
|
- LunarLander-v2 |
|
- ppo |
|
- deep-reinforcement-learning |
|
- reinforcement-learning |
|
- custom-implementation |
|
- deep-rl-course |
|
model-index: |
|
- name: PPO |
|
results: |
|
- task: |
|
type: reinforcement-learning |
|
name: reinforcement-learning |
|
dataset: |
|
name: LunarLander-v2 |
|
type: LunarLander-v2 |
|
metrics: |
|
- type: mean_reward |
|
value: -26.75 +/- 72.19 |
|
name: mean_reward |
|
verified: false |
|
--- |
|
|
|
# PPO Agent Playing LunarLander-v2 |
|
|
|
This is a trained model of a PPO agent playing LunarLander-v2. |
|
|
|
# Hyperparameters |
|
```python |
|
{'seed': 1 |
|
'env_id': 'LunarLander-v2' |
|
'total_timesteps': 100000 |
|
'num_envs': 8 |
|
'num_steps': 128 |
|
'gamma': 0.99 |
|
'gae_lambda': 0.95 |
|
'learning_rate': 0.0003 |
|
'clip_range': 0.2 |
|
'value_loss_coef': 0.5 |
|
'entropy_loss_coef': 0.01 |
|
'max_grad_norm': 0.5 |
|
'update_epochs': 4 |
|
'mini_batch_size': 64 |
|
'eval_freq': 10 |
|
'no_cuda': False |
|
'repo_id': 'jrauch/ppo-{env}'} |
|
``` |
|
|
