
# **PPO** Agent playing **InvertedDoublePendulum-v2**
This is a trained model of a **PPO** agent playing **InvertedDoublePendulum-v2**
using the [stable-baselines3 library](https://github.com/DLR-RM/stable-baselines3)
and the [RL Zoo](https://github.com/DLR-RM/rl-baselines3-zoo).

The RL Zoo is a training framework for Stable Baselines3
reinforcement learning agents,
with hyperparameter optimization and pre-trained agents included.

## Usage (with SB3 RL Zoo)

RL Zoo: https://github.com/DLR-RM/rl-baselines3-zoo<br/>
SB3: https://github.com/DLR-RM/stable-baselines3<br/>
SB3 Contrib: https://github.com/Stable-Baselines-Team/stable-baselines3-contrib

Install the RL Zoo (with SB3 and SB3-Contrib):
```bash
pip install rl_zoo3
```

```
# Download model and save it into the logs/ folder
python -m rl_zoo3.load_from_hub --algo ppo --env InvertedDoublePendulum-v2 -orga qgallouedec -f logs/
python -m rl_zoo3.enjoy --algo ppo --env InvertedDoublePendulum-v2  -f logs/
```

If you installed the RL Zoo3 via pip (`pip install rl_zoo3`), from anywhere you can do:
```
python -m rl_zoo3.load_from_hub --algo ppo --env InvertedDoublePendulum-v2 -orga qgallouedec -f logs/
python -m rl_zoo3.enjoy --algo ppo --env InvertedDoublePendulum-v2  -f logs/
```

## Training (with the RL Zoo)
```
python -m rl_zoo3.train --algo ppo --env InvertedDoublePendulum-v2 -f logs/
# Upload the model and generate video (when possible)
python -m rl_zoo3.push_to_hub --algo ppo --env InvertedDoublePendulum-v2 -f logs/ -orga qgallouedec
```

## Hyperparameters
```python
OrderedDict([('batch_size', 512),
             ('clip_range', 0.4),
             ('ent_coef', 1.05057e-06),
             ('gae_lambda', 0.8),
             ('gamma', 0.98),
             ('learning_rate', 0.000155454),
             ('max_grad_norm', 0.5),
             ('n_envs', 1),
             ('n_epochs', 10),
             ('n_steps', 128),
             ('n_timesteps', 1000000.0),
             ('normalize', True),
             ('policy', 'MlpPolicy'),
             ('vf_coef', 0.695929),
             ('normalize_kwargs', {'norm_obs': True, 'norm_reward': False})])
```

{"library_name": "stable-baselines3", "tags": ["InvertedDoublePendulum-v2", "deep-reinforcement-learning", "reinforcement-learning", "stable-baselines3"], "model-index": [{"name": "PPO", "results": [{"task": {"type": "reinforcement-learning", "name": "reinforcement-learning"}, "dataset": {"name": "InvertedDoublePendulum-v2", "type": "InvertedDoublePendulum-v2"}, "metrics": [{"type": "mean_reward", "value": "1507.50 +/- 1434.81", "name": "mean_reward", "verified": false}]}]}]}
stable-baselines3 InvertedDoublePendulum-v2 deep-reinforcement-learning reinforcement-learning model-index region:us
TAGS
#stable-baselines3 #InvertedDoublePendulum-v2 #deep-reinforcement-learning #reinforcement-learning #model-index #region-us 


# PPO Agent playing InvertedDoublePendulum-v2
This is a trained model of a PPO agent playing InvertedDoublePendulum-v2
using the stable-baselines3 library
and the RL Zoo.

The RL Zoo is a training framework for Stable Baselines3
reinforcement learning agents,
with hyperparameter optimization and pre-trained agents included.

## Usage (with SB3 RL Zoo)

RL Zoo: URL
SB3: URL
SB3 Contrib: URL

Install the RL Zoo (with SB3 and SB3-Contrib):




If you installed the RL Zoo3 via pip ('pip install rl_zoo3'), from anywhere you can do:


## Training (with the RL Zoo)


## Hyperparameters


# PPO Agent playing InvertedDoublePendulum-v2
This is a trained model of a PPO agent playing InvertedDoublePendulum-v2
using the stable-baselines3 library
and the RL Zoo.

The RL Zoo is a training framework for Stable Baselines3
reinforcement learning agents,
with hyperparameter optimization and pre-trained agents included. ## Usage (with SB3 RL Zoo)

RL Zoo: URL
SB3: URL
SB3 Contrib: URL

Install the RL Zoo (with SB3 and SB3-Contrib):




If you installed the RL Zoo3 via pip ('pip install rl_zoo3'), from anywhere you can do: ## Training (with the RL Zoo) ## Hyperparameters
TAGS
#stable-baselines3 #InvertedDoublePendulum-v2 #deep-reinforcement-learning #reinforcement-learning #model-index #region-us 
 # PPO Agent playing InvertedDoublePendulum-v2
This is a trained model of a PPO agent playing InvertedDoublePendulum-v2
using the stable-baselines3 library
and the RL Zoo.

The RL Zoo is a training framework for Stable Baselines3
reinforcement learning agents,
with hyperparameter optimization and pre-trained agents included. ## Usage (with SB3 RL Zoo)

RL Zoo: URL
SB3: URL
SB3 Contrib: URL

Install the RL Zoo (with SB3 and SB3-Contrib):




If you installed the RL Zoo3 via pip ('pip install rl_zoo3'), from anywhere you can do: ## Training (with the RL Zoo) ## Hyperparameters
TAGS
#stable-baselines3 #InvertedDoublePendulum-v2 #deep-reinforcement-learning #reinforcement-learning #model-index #region-us 
# PPO Agent playing InvertedDoublePendulum-v2
This is a trained model of a PPO agent playing InvertedDoublePendulum-v2
using the stable-baselines3 library
and the RL Zoo.

The RL Zoo is a training framework for Stable Baselines3
reinforcement learning agents,
with hyperparameter optimization and pre-trained agents included.## Usage (with SB3 RL Zoo)

RL Zoo: URL
SB3: URL
SB3 Contrib: URL

Install the RL Zoo (with SB3 and SB3-Contrib):




If you installed the RL Zoo3 via pip ('pip install rl_zoo3'), from anywhere you can do:## Training (with the RL Zoo)## Hyperparameters