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Jones Wong
319c1340cb
* add marvil policy graph * fix typo * add offline optimizer and enable running marwil * fix loss function * add maintaining the moving average of advantage norm * use sync replay optimizer for unifying * remove offline optimizer and use sync replay optimizer * format by yapf * add imitation learning objective * fix according to eric's review * format by yapf * revise * add test data * marwil
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}
}