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--- |
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library_name: stable-baselines3 |
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tags: |
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- Pendulum-v1 |
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- deep-reinforcement-learning |
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- reinforcement-learning |
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- stable-baselines3 |
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model-index: |
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- name: PPO |
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results: |
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- metrics: |
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- type: mean_reward |
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value: -230.42 +/- 142.54 |
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name: mean_reward |
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task: |
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type: reinforcement-learning |
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name: reinforcement-learning |
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dataset: |
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name: Pendulum-v1 |
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type: Pendulum-v1 |
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--- |
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# **PPO** Agent playing **Pendulum-v1** |
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This is a trained model of a **PPO** agent playing **Pendulum-v1** |
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using the [stable-baselines3 library](https://github.com/DLR-RM/stable-baselines3) |
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and the [RL Zoo](https://github.com/DLR-RM/rl-baselines3-zoo). |
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The RL Zoo is a training framework for Stable Baselines3 |
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reinforcement learning agents, |
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with hyperparameter optimization and pre-trained agents included. |
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## Usage (with SB3 RL Zoo) |
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RL Zoo: https://github.com/DLR-RM/rl-baselines3-zoo<br/> |
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SB3: https://github.com/DLR-RM/stable-baselines3<br/> |
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SB3 Contrib: https://github.com/Stable-Baselines-Team/stable-baselines3-contrib |
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``` |
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# Download model and save it into the logs/ folder |
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python -m rl_zoo3.load_from_hub --algo ppo --env Pendulum-v1 -orga sb3 -f logs/ |
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python enjoy.py --algo ppo --env Pendulum-v1 -f logs/ |
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``` |
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## Training (with the RL Zoo) |
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``` |
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python train.py --algo ppo --env Pendulum-v1 -f logs/ |
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# Upload the model and generate video (when possible) |
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python -m rl_zoo3.push_to_hub --algo ppo --env Pendulum-v1 -f logs/ -orga sb3 |
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``` |
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```python |
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from stable_baselines3 import PPO |
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from stable_baselines3.common.env_util import make_vec_env |
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# Create the environment |
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env_id = "Pendulum-v1" |
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env = make_vec_env(env_id, n_envs=1) |
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# Instantiate the agent |
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model = PPO( |
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"MlpPolicy", |
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env, |
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gamma=0.98, |
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# Using https://proceedings.mlr.press/v164/raffin22a.html |
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use_sde=True, |
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sde_sample_freq=4, |
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learning_rate=1e-3, |
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verbose=1, |
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) |
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# Train the agent |
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model.learn(total_timesteps=int(1e5)) |
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``` |
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## Hyperparameters |
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```python |
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OrderedDict([('clip_range', 0.2), |
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('ent_coef', 0.0), |
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('gae_lambda', 0.95), |
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('gamma', 0.9), |
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('learning_rate', 0.001), |
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('n_envs', 4), |
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('n_epochs', 10), |
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('n_steps', 1024), |
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('n_timesteps', 100000.0), |
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('policy', 'MlpPolicy'), |
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('sde_sample_freq', 4), |
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('use_sde', True), |
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('normalize', False)]) |
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``` |
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