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PyTorch version of Stable Baselines, reliable implementations of reinforcement learning algorithms.
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Antonin Raffin 37ab9d10f1 Rescale actions and add action noise
2019-10-07 16:26:03 +02:00
docs Add doc 2019-09-26 11:46:40 +02:00
scripts Bug fixes + add evaluate script 2019-09-06 10:44:55 +02:00
tests Rescale actions and add action noise 2019-10-07 16:26:03 +02:00
torchy_baselines Rescale actions and add action noise 2019-10-07 16:26:03 +02:00
.coveragerc Bug fixes + add evaluate script 2019-09-06 10:44:55 +02:00
.gitignore Refactor: CEM-RL closer to TD3 implementation 2019-09-09 13:43:46 +02:00
LICENSE Init: TD3 2019-09-05 17:29:41 +02:00
README.md Add a parameter to disable ortho init 2019-09-26 16:29:47 +02:00
setup.cfg Bug fixes + add evaluate script 2019-09-06 10:44:55 +02:00
setup.py Working SAC 2019-09-24 14:15:12 +02:00

README.md

Build Status Documentation Status

Torchy Baselines

PyTorch version of Stable Baselines, a set of improved implementations of reinforcement learning algorithms.

Implemented Algorithms

  • CEM-RL (with TD3)
  • PPO
  • SAC
  • TD3

Roadmap

TODO:

  • save/load
  • predict
  • better rescale (min + action * range)
  • flexible mlp
  • logger
  • better monitor wrapper?
  • automatic choice for action distribution
  • A2C

Later:

  • get_parameters / set_parameters
  • CNN policies + normalization
  • tensorboard support
  • DQN
  • TRPO
  • ACER
  • DDPG
  • HER -> use stable-baselines because does not depends on tf?