Files
ray/python/ray/rllib
Jones Wong da7676c925 Removed the implicit sync barrier at the end of each training iteration (#5217)
*  removed sync barrier at the end of each training iteration

*  formatted

*  modify the comment according to current semantics

*  lint check

* Update trainer.py
2019-07-18 22:59:52 -07:00
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RLlib: Scalable Reinforcement Learning

RLlib is an open-source library for reinforcement learning that offers both high scalability and a unified API for a variety of applications.

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}
}