semvec/pypi-packages huggingface dataset:
rlflow 0.1.3
A framework for learning about and experimenting with reinforcement learning algorithms
License: MIT license
Keywords: FLFlow,TFLearn,TensorFlow,Deep Learning,Reinforcement Learning,Machine Learning,Neural Networks

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RLFlow
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A framework for learning about and experimenting with reinforcement learning algorithms.
It is built on top of TensorFlow and `TFLearn <http://tflearn.org/>`_  and is interfaces
with the OpenAI gym (universe should work, too). It aims to be as modular as possible so
that new algorithms and ideas can easily be tested. I started it to gain a better
understanding of core RL algorithms and maybe it can be useful for others as well.


Features
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Algorithms (future algorithms italicized):

  - MDP algorithms

      + Value iteration
      + Policy iteration

  - Temporal Difference Learning

      + SARSA
      + Deep Q-Learning
      + *Policy gradient Q-learning*

  - Gradient algorithms

      + Vanilla policy gradient
      + *Deterministic policy gradient*
      + *Natural policy gradient*

  - Gradient-Free algorithms

      + *Cross entropy method*

Function approximators (defined by TFLearn model):

  - Linear
  - Neural network
  - *RBF*

Works with any OpenAI gym environment.


Future Enhancements
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* Improved TensorBoard logging
* Improved model snapshotting to include exploration states, memories, etc.
* Any suggestions?


Fixes
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* Errors / warnings on TensorFlow session save


License
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* Free software: MIT license
* Documentation: https://rlflow.readthedocs.io.


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History
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0.1.2/3 (2016-17-15)
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* Improving meta data and fixing __init__ scripts to load subpackages properly


0.1.0 (2016-16-15)
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* First release on PyPI.