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RL: Generic reinforcement learning codebase in TensorFlow - Published in JOSS (2019)

https://github.com/Cohere-Labs-Community/rl

Science Score: 59.0%

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    CITATION.cff file
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    codemeta.json file
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    .zenodo.json file
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    DOI references
    Found 3 DOI reference(s) in README
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    Academic publication links
    Links to: joss.theoj.org, zenodo.org
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    Committers with academic emails
    1 of 7 committers (14.3%) from academic institutions
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    Scientific vocabulary similarity
    Low similarity (8.2%) to scientific vocabulary

Keywords

machine-learning reinforcement-learning rl tensorflow

Keywords from Contributors

interpretability mesh interactive
Last synced: 6 months ago · JSON representation

Repository

Generic reinforcement learning codebase in TensorFlow

Basic Info
  • Host: GitHub
  • Owner: Cohere-Labs-Community
  • License: mit
  • Language: Python
  • Default Branch: master
  • Homepage:
  • Size: 9.49 MB
Statistics
  • Stars: 95
  • Watchers: 9
  • Forks: 21
  • Open Issues: 1
  • Releases: 2
Topics
machine-learning reinforcement-learning rl tensorflow
Created almost 7 years ago · Last pushed over 4 years ago
Metadata Files
Readme License

README.md

FOR.ai Reinforcement Learning Codebase status DOI Build Status

Modular codebase for reinforcement learning models training, testing and visualization.

Contributors: Bryan M. Li, Alexander Cowen-Rivers, Piotr Kozakowski, David Tao, Siddhartha Rao Kamalakara, Nitarshan Rajkumar, Hariharan Sezhiyan, Sicong Huang, Aidan N. Gomez

Features

Example for recorded envrionment on various RL agents.

| MountainCar-v0 | Pendulum-v0 | VideoPinball-v0 | procgen-coinrun-v0 | | -------------------------------------- | -------------------------------- | ----------------------------------- | ----------------------------- | | MountainCar-v0 | Pendulum-v0 | VideoPinball-v0 | Tennis-v0 |

Requirements

It is recommended to install the codebase in a virtual environment (virtualenv or conda).

Quick install

Configure use_gpu and (if on OSX) mac_package_manager (either macports or homebrew) params in setup.sh, then run it as bash sh setup.sh

Manual setup

You need to install the following for your system:

Quick Start

```

start training

python train.py --sys ... --hparams ... --output_dir ...

run tensorboard

tensorboard --logdir ...

test agnet

python train.py --sys ... --hparams ... --outputdir ... --testonly --render ```

Hyper-parameters

Check available flags with --help, defaults.py for default hyper-parameters, and check hparams/dqn.py agent specific hyper-parameters examples. - hparams: Which hparams to use, defined under rl/hparams - sys: Which system environment to use. - env: Which RL environment to use. - output_dir: The directory for model checkpoints and TensorBoard summary. - train_steps:, Number of steps to train the agent. - test_episodes: Number of episodes to test the agent. - eval_episodes: Number of episodes to evaluate the agent. - test_only: Test agent without training. - copies: Number of independent training/testing runs to do. - render: Render game play. - record_video: Record game play. - num_workers, number of workers.

Documentation

More detailed documentation can be found here.

Contributing

We'd love to accept your contributions to this project. Please feel free to open an issue, or submit a pull request as necessary. Contact us team@for.ai for potential collaborations and joining FOR.ai.

Owner

  • Name: Cohere Labs Community
  • Login: Cohere-Labs-Community
  • Kind: organization
  • Email: info@for.ai
  • Location: Toronto, Canada

Cohere Labs is Cohere's non-profit research lab that seeks to solve complex ML problems and are focused on creating more points of entry to the field.

GitHub Events

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Committers

Last synced: 7 months ago

All Time
  • Total Commits: 44
  • Total Committers: 7
  • Avg Commits per committer: 6.286
  • Development Distribution Score (DDS): 0.636
Past Year
  • Commits: 0
  • Committers: 0
  • Avg Commits per committer: 0.0
  • Development Distribution Score (DDS): 0.0
Top Committers
Name Email Commits
Alexander Cowen-Rivers m****s@i****m 16
Bryan M. Li b****y@g****m 13
Hari h****n@u****u 8
Sheldon h****r@g****m 3
Amr M. Kayid a****7@g****m 2
dependabot[bot] 4****] 1
Kyle Niemeyer k****r@g****m 1
Committer Domains (Top 20 + Academic)
ucdavis.edu: 1

Issues and Pull Requests

Last synced: 6 months 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

docs/requirements.txt pypi
  • sphinx ==2.1.2
  • sphinx_rtd_theme *
  • sphinxcontrib-bibtex *
requirements.txt pypi
  • atari_py ==0.1.7
  • box2d-py *
  • cleverhans de5db266fdf47830f46c80cca53fd84fbbb542bf
  • dl-cloud *
  • gym ==0.15.4
  • opencv-python ==3.4.2.17
  • procgen ==0.9.2
  • requests ==2.20.0
  • roboschool *
  • tqdm *