TF2-RL
Reinforcement learning algorithms implemented for Tensorflow 2.0+ [DQN, DDPG, AE-DDPG, SAC, PPO, Primal-Dual DDPG]
Train reinforcement learning models using various algorithms in TensorFlow with example code.
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Free · no card · unsubscribe anytimeReinforcement learning algorithms implemented for Tensorflow 2.0+ [DQN, DDPG, AE-DDPG, SAC, PPO, Primal-Dual DDPG]
TF2-RL has 316 stars on GitHub. It has been forked 66 times. TF2-RL is written mainly in Python. It has been in active development since 2020. TF2-RL is available under the MIT license. Its main topics are ae-ddpg, ddpg, dqn, openai-gym.
What is TF2-RL?
Reinforcement learning algorithms implemented for Tensorflow 2.0+ [DQN, DDPG, AE-DDPG, SAC, PPO, Primal-Dual DDPG]
Is TF2-RL open source?
TF2-RL is an open-source project. It is released under the MIT license.
Is TF2-RL free?
Yes. TF2-RL is free and open source — you can use, modify and self-host it.
What license does TF2-RL use?
TF2-RL is available under the MIT license.
What language is TF2-RL written in?
TF2-RL is written mainly in Python.
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