rlberry
An easy-to-use reinforcement learning library for research and education.
Science Score: 67.0%
This score indicates how likely this project is to be science-related based on various indicators:
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✓CITATION.cff file
Found CITATION.cff file -
✓codemeta.json file
Found codemeta.json file -
✓.zenodo.json file
Found .zenodo.json file -
✓DOI references
Found 1 DOI reference(s) in README -
○Academic publication links
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✓Committers with academic emails
3 of 25 committers (12.0%) from academic institutions -
○Institutional organization owner
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○JOSS paper metadata
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○Scientific vocabulary similarity
Low similarity (17.1%) to scientific vocabulary
Keywords
Keywords from Contributors
Repository
An easy-to-use reinforcement learning library for research and education.
Basic Info
- Host: GitHub
- Owner: rlberry-py
- License: mit
- Language: Python
- Default Branch: main
- Homepage: https://rlberry-py.github.io/rlberry
- Size: 18.6 MB
Statistics
- Stars: 169
- Watchers: 7
- Forks: 30
- Open Issues: 40
- Releases: 12
Topics
Metadata Files
README.md
A Reinforcement Learning Library for Research and Education
What is rlberry?
Writing reinforcement learning algorithms is fun! But after the fun, we have lots of boring things to implement: run our agents in parallel, average and plot results, optimize hyperparameters, compare to baselines, create tricky environments etc etc!
rlberry is a Python library that makes your life easier by doing all these things with a few lines of code, so
that you can spend most of your time developing agents.
rlberry also provides implementations of several RL agents, benchmark environments and many other useful tools.
We provide you a number of tools to help you achieve reproducibility, statistically comparisons of RL agents, and nice visualization.
Installation
Install the latest (minimal) version for a stable release.
bash
pip install -U rlberry
The documentation includes more installation instructions.
Getting started
In our dev documentation, you will find quick starts to the library and a user guide with a few tutorials on using rlberry, and some examples. See also the stable documentation for the documentation corresponding to the last release.
Changelog
See the changelog for a history of the changes made to rlberry.
Other rlberry projects
rlberry-scool : It’s the repository used for teaching purposes. These are mainly basic agents and environments, in a version that makes it easier for students to learn.
rlberry-research : It’s the repository where our research team keeps some agents, environments, or tools compatible with rlberry. It’s a permanent “work in progress” repository, and some code may be not maintained anymore.
Citing rlberry
If you use rlberry in scientific publications, we would appreciate citations using the following Bibtex entry:
bibtex
@misc{rlberry,
author = {Domingues, Omar Darwiche and Flet-Berliac, Yannis and Leurent, Edouard and M{\'e}nard, Pierre and Shang, Xuedong and Valko, Michal},
doi = {10.5281/zenodo.5544540},
month = {10},
title = {{rlberry - A Reinforcement Learning Library for Research and Education}},
url = {https://github.com/rlberry-py/rlberry},
year = {2021}
}
About us
This project was initiated and is actively maintained by INRIA SCOOL team. More information here.
Contributing
Want to contribute to rlberry? Please check our contribution guidelines. If you want to add any new agents or environments, do not hesitate
to open an issue!
Owner
- Name: rlberry-py
- Login: rlberry-py
- Kind: organization
- Repositories: 1
- Profile: https://github.com/rlberry-py
Citation (CITATION.cff)
cff-version: 1.2.0 message: "If you use this software, please cite it as below." authors: - family-names: "Domingues" given-names: "Omar Darwiche" - family-names: "Flet-Berliac" given-names: "Yannis" - family-names: "Leurent" given-names: "Edouard" - family-names: "Ménard" given-names: "Pierre" - family-names: "Shang" given-names: "Xuedong" - family-names: "Valko" given-names: "Michal" title: "rlberry - A Reinforcement Learning Library for Research and Education" abbreviation: rlberry version: 0.2.2-dev doi: 10.5281/zenodo.5223307 date-released: 2021-10-01 url: "https://github.com/rlberry-py/rlberry"
GitHub Events
Total
- Issues event: 2
- Watch event: 8
- Issue comment event: 42
- Push event: 61
- Pull request event: 8
- Pull request review comment event: 12
- Pull request review event: 11
Last Year
- Issues event: 2
- Watch event: 8
- Issue comment event: 42
- Push event: 61
- Pull request event: 8
- Pull request review comment event: 12
- Pull request review event: 11
Committers
Last synced: about 1 year ago
Top Committers
| Name | Commits | |
|---|---|---|
| Omar D | o****h@g****m | 441 |
| TimotheeMathieu | t****u@i****r | 235 |
| xuedong | s****g@y****r | 146 |
| Ju T | 5****1 | 94 |
| Edouard Leurent | e****t@g****m | 77 |
| yfletberliac | y****e@g****m | 65 |
| sauxpa | p****x@g****m | 27 |
| Matheus M. Centa | m****a@g****m | 18 |
| KohlerHECTOR | K****R | 16 |
| sauxpa | p****x@i****r | 8 |
| AleShi94 | a****a@s****u | 6 |
| Pierre Ménard | m****r@g****m | 6 |
| Riccardo Della Vecchia | r****1@g****m | 6 |
| Hector Kohler | h****r@u****n | 6 |
| Rémy Degenne | r****e@g****m | 4 |
| Antoine Moulin | a****n@t****r | 4 |
| pre-commit-ci[bot] | 6****] | 3 |
| Waris Radji | w****4@g****m | 2 |
| brahimdriss | b****s | 2 |
| TimotheeMathieu | t****u@u****r | 2 |
| dependabot[bot] | 4****] | 1 |
| YannBerthelot | 4****t | 1 |
| The Codacy Badger | b****r@c****m | 1 |
| Boris Hamadej | 9****j | 1 |
| AdrienneTuynman | 1****n | 1 |
Committer Domains (Top 20 + Academic)
Issues and Pull Requests
Last synced: 6 months ago
All Time
- Total issues: 53
- Total pull requests: 126
- Average time to close issues: 4 months
- Average time to close pull requests: about 1 month
- Total issue authors: 7
- Total pull request authors: 17
- Average comments per issue: 0.89
- Average comments per pull request: 3.37
- Merged pull requests: 87
- Bot issues: 0
- Bot pull requests: 18
Past Year
- Issues: 1
- Pull requests: 9
- Average time to close issues: N/A
- Average time to close pull requests: 9 days
- Issue authors: 1
- Pull request authors: 2
- Average comments per issue: 0.0
- Average comments per pull request: 5.67
- Merged pull requests: 6
- Bot issues: 0
- Bot pull requests: 0
Top Authors
Issue Authors
- TimotheeMathieu (29)
- JulienT01 (9)
- KohlerHECTOR (5)
- mmcenta (2)
- RemyDegenne (2)
- YannBerthelot (2)
- riiswa (2)
- AleShi94 (1)
Pull Request Authors
- JulienT01 (71)
- TimotheeMathieu (56)
- dependabot[bot] (14)
- KohlerHECTOR (6)
- pre-commit-ci[bot] (4)
- RemyDegenne (3)
- riiswa (3)
- AdrienneTuynman (2)
- akrouriad (1)
- BorisHamadej (1)
- riccardodv (1)
- YannBerthelot (1)
- brahimdriss (1)
- omardrwch (1)
- AmirAflak (1)
Top Labels
Issue Labels
Pull Request Labels
Packages
- Total packages: 1
-
Total downloads:
- pypi 187 last-month
- Total dependent packages: 1
- Total dependent repositories: 3
- Total versions: 16
- Total maintainers: 4
pypi.org: rlberry
An easy-to-use reinforcement learning library for research and education
- Homepage: https://github.com/rlberry-py
- Documentation: https://rlberry.readthedocs.io/
- License: LICENSE
-
Latest release: 0.7.3
published almost 2 years ago
Rankings
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