RLToolkit is a flexible and high-efficient reinforcement learning framework. Include implementation of DQN, AC,A2C, A3C, PG, DDPG, TRPO, PPO, SAC, TD3 and ....
APACHE-2.0 License
Deep RL Toolkit is a flexible and high-efficient reinforcement learning framework. RLToolkit is developed for practitioners with the following advantages:
Reproducible. We provide algorithms that stably reproduce the result of many influential reinforcement learning algorithms.
Extensible. Build new algorithms quickly by inheriting the abstract class in the framework.
Reusable. Algorithms provided in the repository could be directly adapted to a new task by defining a forward network and training mechanism will be built automatically.
Elastic: allows to elastically and automatically allocate computing resources on the cloud.
Lightweight: the core codes <1,000 lines (check Demo).
Stable: much more stable than Stable Baselines 3 by utilizing various ensemble methods.
RLToolkit implements the following model-free deep reinforcement learning (DRL) algorithms:
For the details of DRL algorithms, please check out the educational webpage OpenAI Spinning Up.
If you want to learn more about deep reinforcemnet learning, please read the deep-rl-class and run the examples.
git clone https://github.com/jianzhnie/deep-rl-toolkit.git
# Run the DQN algorithm on the CartPole-v0 environment
python examples/cleanrl/cleanrl_runner.py --env CartPole-v0 --algo dqn
python examples/cleanrl/cleanrl_runner.py --env CartPole-v0 --algo ddqn
python examples/cleanrl/cleanrl_runner.py --env CartPole-v0 --algo dueling_dqn
python examples/cleanrl/cleanrl_runner.py --env CartPole-v0 --algo dueling_ddqn
# Run the C51 algorithm on the CartPole-v0 environment
python examples/cleanrl/cleanrl_runner.py --env CartPole-v0 --algo c51
# Run the DDPG algorithm on the Pendulum-v1 environment
python examples/cleanrl/cleanrl_runner.py --env Pendulum-v0 --algo ddpg
# Run the PPO algorithm on the CartPole-v0 environment
python examples/cleanrl/cleanrl_runner.py --env CartPole-v0 --algo ppo
rllib
coach
Pearl
tianshou
stable-baselines3
PARL
openrl
cleanrl