ray/rllib
2020-11-26 13:14:11 +01:00
..
agents [RLlib] Torch LR schedule not working. Fix and added test case. (#12396) 2020-11-26 13:14:11 +01:00
contrib [docs] Move all /latest links to /master (#11897) 2020-11-10 10:53:28 -08:00
env [RLlib] Add ResetOnExceptionWrapper with tests for unstable 3rd party envs (#12353) 2020-11-25 08:41:58 +01:00
evaluation [RLlib] Issue 12118: LSTM prev-a/r should be separately configurable. Fix missing prev-a one-hot encoding. (#12397) 2020-11-25 11:27:46 -08:00
examples [RLlib] Issue 12118: LSTM prev-a/r should be separately configurable. Fix missing prev-a one-hot encoding. (#12397) 2020-11-25 11:27:46 -08:00
execution [RLlib] Trajectory view API: Enable by default for PPO, IMPALA, PG, A3C (tf and torch). (#11747) 2020-11-12 16:27:34 +01:00
models [RLlib] Issue 12118: LSTM prev-a/r should be separately configurable. Fix missing prev-a one-hot encoding. (#12397) 2020-11-25 11:27:46 -08:00
offline [RLlib] Fix offline logp vs prob bug in OffPolicyEstimator class. (#12158) 2020-11-20 08:59:43 +01:00
policy [RLlib] Torch LR schedule not working. Fix and added test case. (#12396) 2020-11-26 13:14:11 +01:00
tests [RLlib] Issue 12118: LSTM prev-a/r should be separately configurable. Fix missing prev-a one-hot encoding. (#12397) 2020-11-25 11:27:46 -08:00
tuned_examples [RLlib] Increase the scope of RLlib's regression tests. (#12200) 2020-11-24 22:18:31 +01:00
utils [RLlib] Issue 12118: LSTM prev-a/r should be separately configurable. Fix missing prev-a one-hot encoding. (#12397) 2020-11-25 11:27:46 -08:00
__init__.py [RLlib] First attempt at cleaning up algo code in RLlib: PG. (#10115) 2020-08-20 17:05:57 +02:00
asv.conf.json [rllib] Try moving RLlib to top level dir (#5324) 2019-08-05 23:25:49 -07:00
BUILD [RLlib] Issue 12118: LSTM prev-a/r should be separately configurable. Fix missing prev-a one-hot encoding. (#12397) 2020-11-25 11:27:46 -08:00
README.md [docs] Move all /latest links to /master (#11897) 2020-11-10 10:53:28 -08:00
rollout.py [RLlib] rollout batch, handle rewards that are None (unknown) in a multi-agent env (#11858) (#11911) 2020-11-25 13:39:22 +01:00
scripts.py [RLlib] Deprecate old classes, methods, functions, config keys (in prep for RLlib 1.0). (#10544) 2020-09-06 10:58:00 +02:00
train.py [tune] move _SCHEDULERS to tune.schedulers and add all available schedulers (#11218) 2020-10-08 16:10:23 -07:00

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}
}

Development Install

You can develop RLlib locally without needing to compile Ray by using the setup-dev.py script. This sets up links between the rllib dir in your git repo and the one bundled with the ray package. When using this script, make sure that your git branch is in sync with the installed Ray binaries (i.e., you are up-to-date on master and have the latest wheel installed.)