DQN Agent playing Acrobot-v1
This is a trained model of a DQN agent playing Acrobot-v1 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 dqn --env Acrobot-v1 -orga sb3 -f logs/
python enjoy.py --algo dqn --env Acrobot-v1 -f logs/
Training (with the RL Zoo)
python train.py --algo dqn --env Acrobot-v1 -f logs/
# Upload the model and generate video (when possible)
python -m rl_zoo3.push_to_hub --algo dqn --env Acrobot-v1 -f logs/ -orga sb3
Hyperparameters
OrderedDict([('batch_size', 128),
('buffer_size', 50000),
('exploration_final_eps', 0.1),
('exploration_fraction', 0.12),
('gamma', 0.99),
('gradient_steps', -1),
('learning_rate', 0.00063),
('learning_starts', 0),
('n_timesteps', 100000.0),
('policy', 'MlpPolicy'),
('policy_kwargs', 'dict(net_arch=[256, 256])'),
('target_update_interval', 250),
('train_freq', 4),
('normalize', False)])