Files
ray/python/ray/rllib
Jones Wong 3ac8fd7ee8 Exploration with Parameter Space Noise (#4048)
*  enable parameter space noise for exploration

*  enable parameter space noise for exploration

*  yapf formatted

*  remove the usage of scipy softmax avialable in the latest version only

*  enable subclass that has no parameter_noise in the config

*  run user specified callbacks and test parameter space noise in multi node setting

*  formatted by yapf

* Update dqn.py

* lint
2019-02-20 22:35:18 -08:00
..

RLlib: Scalable Reinforcement Learning

RLlib is an open-source library for reinforcement learning that offers both a collection of reference algorithms and scalable primitives for composing new ones.

For an overview of RLlib, see the documentation.

If you've found RLlib useful for your research, you can cite the paper as follows:

@inproceedings{liang2018rllib,
    Author = {Eric Liang and
              Richard Liaw and
              Robert Nishihara and
              Philipp Moritz and
              Roy Fox and
              Ken Goldberg and
              Joseph E. Gonzalez and
              Michael I. Jordan and
              Ion Stoica},
    Title = {{RLlib}: Abstractions for Distributed Reinforcement Learning},
    Booktitle = {International Conference on Machine Learning ({ICML})},
    Year = {2018}
}