|
--- |
|
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: -157.06 +/- 48.98 |
|
name: mean_reward |
|
verified: false |
|
--- |
|
|
|
# PPO Agent Playing LunarLander-v2 |
|
|
|
This is a trained model of a PPO agent playing LunarLander-v2. |
|
|
|
# Hyperparameters |
|
```python |
|
{'env_id': 'LunarLander-v2' |
|
'n_envs': 8 |
|
'n_steps': 128 |
|
'epochs': 4 |
|
'lr': 1e-05 |
|
'gamma': 0.99 |
|
'n_minibatches': 4 |
|
'batch_size': 1024 |
|
'minibatch_size': 256 |
|
'total_timesteps': 10000000 |
|
'n_iterations': 9765 |
|
'norm_adv': True |
|
'epsilon': 0.2 |
|
'clip_vloss': True |
|
'vf_coef': 0.5 |
|
'ent_coef': 0.01} |
|
``` |
|
|