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sb3/
ppo-ReacherBulletEnv-v0

Name: ppo-ReacherBulletEnv-v0
Availability: InStock

stable-baselines3

ReacherBulletEnv-v0

deep-reinforcement-learning

reinforcement-learning

model-index

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PPO Agent playing ReacherBulletEnv-v0

This is a trained model of a PPO agent playing ReacherBulletEnv-v0 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: https://github.com/DLR-RM/rl-baselines3-zoo
SB3: https://github.com/DLR-RM/stable-baselines3
SB3 Contrib: https://github.com/Stable-Baselines-Team/stable-baselines3-contrib

# Download model and save it into the logs/ folder
python -m rl_zoo3.load_from_hub --algo ppo --env ReacherBulletEnv-v0 -orga sb3 -f logs/
python enjoy.py --algo ppo --env ReacherBulletEnv-v0  -f logs/

Training (with the RL Zoo)

python train.py --algo ppo --env ReacherBulletEnv-v0 -f logs/
# Upload the model and generate video (when possible)
python -m rl_zoo3.push_to_hub --algo ppo --env ReacherBulletEnv-v0 -f logs/ -orga sb3

Hyperparameters

python

OrderedDict([('batch_size', 64),
             ('clip_range', 'lin_0.4'),
             ('ent_coef', 0.0),
             ('env_wrapper', 'sb3_contrib.common.wrappers.TimeFeatureWrapper'),
             ('gae_lambda', 0.9),
             ('gamma', 0.99),
             ('learning_rate', 3e-05),
             ('max_grad_norm', 0.5),
             ('n_envs', 8),
             ('n_epochs', 20),
             ('n_steps', 512),
             ('n_timesteps', 1000000.0),
             ('normalize', True),
             ('policy', 'MlpPolicy'),
             ('policy_kwargs',
              'dict(log_std_init=-2.7, ortho_init=False, '
              'activation_fn=nn.ReLU, net_arch=[dict(pi=[256, 256], vf=[256, '
              '256])] )'),
             ('sde_sample_freq', 4),
             ('use_sde', True),
             ('vf_coef', 0.5),
             ('normalize_kwargs', {'norm_obs': True, 'norm_reward': False})])

sb3/ppo-ReacherBulletEnv-v0

PPO Agent playing ReacherBulletEnv-v0

Usage (with SB3 RL Zoo)

Training (with the RL Zoo)

Hyperparameters

sb3/
ppo-ReacherBulletEnv-v0