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Open Source Science

https://github.com/blutjens/rllab

rllab is a framework for developing and evaluating reinforcement learning algorithms, fully compatible with OpenAI Gym.

https://github.com/blutjens/rllab

Science Score: 20.0%

This score indicates how likely this project is to be science-related based on various indicators:

  • ○
    CITATION.cff file
  • ○
    codemeta.json file
  • ○
    .zenodo.json file
  • ○
    DOI references
  • ✓
    Academic publication links
    Links to: arxiv.org
  • ✓
    Committers with academic emails
    4 of 32 committers (12.5%) from academic institutions
  • ○
    Institutional organization owner
  • ○
    JOSS paper metadata
  • ○
    Scientific vocabulary similarity
    Low similarity (13.7%) to scientific vocabulary

Keywords from Contributors

reinforcement-learning gym deep-neural-networks distributed tensor keras mxnet apache-mxnet keras-mxnet keras-neural-networks
Last synced: 6 months ago · JSON representation

Repository

rllab is a framework for developing and evaluating reinforcement learning algorithms, fully compatible with OpenAI Gym.

Basic Info
  • Host: GitHub
  • Owner: blutjens
  • License: other
  • Language: Python
  • Default Branch: master
  • Homepage:
  • Size: 847 MB
Statistics
  • Stars: 0
  • Watchers: 1
  • Forks: 0
  • Open Issues: 0
  • Releases: 0
Fork of rll/rllab
Created over 6 years ago · Last pushed over 6 years ago
Metadata Files
Readme Changelog License

README.md

rllab is no longer under active development, but an alliance of researchers from several universities has adopted it, and now maintains it under the name garage.

We recommend you develop new projects, and rebase old ones, onto the actively-maintained garage codebase, to promote reproducibility and code-sharing in RL research. The new codebase shares almost all of its code with rllab, so most conversions only need to edit package import paths and perhaps update some renamed functions.

garage is always looking for new users and contributors, so please consider contributing your rllab-based projects and improvements to the new codebase! Recent improvements include first-class support for TensorFlow, TensorBoard integration, new algorithms including PPO and DDPG, updated Docker images, new environment wrappers, many updated dependencies, and stability improvements.

Docs Circle CI License Join the chat at https://gitter.im/rllab/rllab

rllab

rllab is a framework for developing and evaluating reinforcement learning algorithms. It includes a wide range of continuous control tasks plus implementations of the following algorithms:

rllab is fully compatible with OpenAI Gym. See here for instructions and examples.

rllab only officially supports Python 3.5+. For an older snapshot of rllab sitting on Python 2, please use the py2 branch.

rllab comes with support for running reinforcement learning experiments on an EC2 cluster, and tools for visualizing the results. See the documentation for details.

The main modules use Theano as the underlying framework, and we have support for TensorFlow under sandbox/rocky/tf.

Documentation

Documentation is available online: https://rllab.readthedocs.org/en/latest/.

Citing rllab

If you use rllab for academic research, you are highly encouraged to cite the following paper:

Credits

rllab was originally developed by Rocky Duan (UC Berkeley / OpenAI), Peter Chen (UC Berkeley), Rein Houthooft (UC Berkeley / OpenAI), John Schulman (UC Berkeley / OpenAI), and Pieter Abbeel (UC Berkeley / OpenAI). The library is continued to be jointly developed by people at OpenAI and UC Berkeley.

Slides

Slides presented at ICML 2016: https://www.dropbox.com/s/rqtpp1jv2jtzxeg/ICML2016benchmarkingslides.pdf?dl=0

Owner

  • Name: Björn Lütjens (he/him)
  • Login: blutjens
  • Kind: user
  • Company: MIT

Postdoctoral Associate in tackling climate change with AI @ MIT. Project overview at https://blutjens.github.io/

GitHub Events

Total
Last Year

Committers

Last synced: about 2 years ago

All Time
  • Total Commits: 138
  • Total Committers: 32
  • Avg Commits per committer: 4.313
  • Development Distribution Score (DDS): 0.449
Past Year
  • Commits: 0
  • Committers: 0
  • Avg Commits per committer: 0.0
  • Development Distribution Score (DDS): 0.0
Top Committers
Name Email Commits
Rocky Duan d****k@g****m 76
Rocky Duan d****k 12
Vitchyr Pong v****r@g****m 9
sytham m****l@g****m 7
Peter Henderson B****d 5
Alex Beloi a****i 2
Alex Beloi a****i@s****m 2
haarnoja h****a 1
Hyun Oh Song r****l 1
Brandon Amos b****s@v****u 1
Dr. Kashif Rasul k****l@g****m 1
Aishwarya Unnikrishnan s****n@g****m 1
Xiaohu Zhu x****u@g****m 1
bichengcao b****o@g****m 1
inksci i****i@q****m 1
Aman Soni g****e@a****m 1
lchenat l****t@c****k 1
Ben c****n 1
ViktorM v****k@g****m 1
Paul Hendricks p****3@o****u 1
OpenAI server s****s@o****m 1
Mickaël Fourgeaud m****d@g****m 1
John Co-Reyes j****s@g****m 1
Carlos Florensa f****c 1
Zhongwen Xu z****u@g****m 1
David Held d****d@e****u 1
Daniel Marta d****a@g****m 1
Yang Song y****g 1
Gunjan Baid g****d 1
chang cheng m****a@g****m 1
and 2 more...
Committer Domains (Top 20 + Academic)
gmu.edu: 1 eecs.berkeley.edu: 1 openai.com: 1 owu.edu: 1 connect.ust.hk: 1 amansoni.com: 1 qq.com: 1 vt.edu: 1 samsung.com: 1

Issues and Pull Requests

Last synced: about 2 years ago

All Time
  • Total issues: 0
  • Total pull requests: 0
  • Average time to close issues: N/A
  • Average time to close pull requests: N/A
  • Total issue authors: 0
  • Total pull request authors: 0
  • Average comments per issue: 0
  • Average comments per pull request: 0
  • Merged pull requests: 0
  • Bot issues: 0
  • Bot pull requests: 0
Past Year
  • Issues: 0
  • Pull requests: 0
  • Average time to close issues: N/A
  • Average time to close pull requests: N/A
  • Issue authors: 0
  • Pull request authors: 0
  • Average comments per issue: 0
  • Average comments per pull request: 0
  • Merged pull requests: 0
  • Bot issues: 0
  • Bot pull requests: 0
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Dependencies

docker/Dockerfile docker
  • ubuntu 16.04 build
environment.yml pypi
  • Cython *
  • Lasagne 484866cf8b38d878e92d521be445968531646bb8
  • Pillow *
  • PyOpenGL *
  • Theano adfe319ce6b781083d8dc3200fb4481b00853791
  • atari-py *
  • awscli *
  • boto3 *
  • cached_property *
  • chainer ==1.18.0
  • cloudpickle *
  • gym v0.7.4
  • hyperopt *
  • ipdb *
  • jupyter *
  • keras ==1.2.1
  • line_profiler *
  • msgpack-python *
  • nibabel ==2.1.0
  • nose2 *
  • numpy-stl ==2.2.0
  • plotly 2594076e29584ede2d09f2aa40a8a195b3f3fc66
  • polling *
  • progressbar2 *
  • pyglet *
  • pylru ==1.0.9
  • pyprind *
  • pyzmq *
  • redis *
  • tqdm *
setup.py pypi
rllab/mujoco_py/Gemfile rubygems
  • activesupport >= 0
  • pry >= 0
rllab/mujoco_py/Gemfile.lock rubygems
  • activesupport 4.1.8
  • coderay 1.1.0
  • i18n 0.7.0
  • json 1.8.1
  • method_source 0.8.2
  • minitest 5.5.1
  • pry 0.10.1
  • slop 3.6.0
  • thread_safe 0.3.4
  • tzinfo 1.2.2