[](https://travis-ci.com/hill-a/stable-baselines) [](https://stable-baselines.readthedocs.io/en/master/?badge=master) # Torchy Baselines PyTorch version of [Stable Baselines](https://github.com/hill-a/stable-baselines), a set of improved implementations of reinforcement learning algorithms. ## Implemented Algorithms - A2C - CEM-RL (with TD3) - PPO - SAC - TD3 ## Roadmap TODO: - save/load - better predict - complete logger - SDE: reduce the number of parameters (only n_features instead of n_features x n_actions) for A2C (done for TD3) - SDE: learn the feature extractor? Later: - get_parameters / set_parameters - CNN policies + normalization - tensorboard support - DQN - TRPO - ACER - DDPG - HER -> use stable-baselines because does not depends on tf?