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Repository for Open Source Reinforcement Learning Framework JORLDY
| Date | Stars |
|---|---|
| 2026-07-31 | 365 |
| 2026-08-04 | 365 |
| 2026-08-05 | 365 |
| 2026-08-06 | 365 |
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# JORLDY (Beta) [](LICENSE) Hello Wo**RL**d!!:hand: **Join Our Reinforcement Learning framework for Developing Yours (JORLDY)** is an open-source Reinforcement Learning (RL) framework provided by [KakaoEnterprise](https://www.kakaoenterprise.com/). It is named after Jordy, one of the [Kakao Niniz](https://www.kakaocorp.com/page/service/service/Niniz) character. It provides various RL algorithms and environment and they can be easily used using single code. This repository is opened for helping RL researchers and students who study RL. ## :fire: Features - 20+ RL Algorithms and various RL environment are provided - Algorithms and environment are customizable - New algorithms and environment can be added - Distributed RL algorithms are provided using [ray](https://github.com/ray-project/ray) - Benchmark of the algorithms is conducted in many RL environment ## :heavy_check_mark: Tested | Python | Windows | Mac | Linux | | :----: | :---------: | :-----: | :------: | | 3.8<br />3.7 | Windows Server 2022 | macOS Big Sur 11<br />macOS Catalina 10.15 | Ubuntu 20.04<br />Ubuntu 18.04 | ## :arrow_down: Installation ``` git clone https://github.com/kakaoenterprise/JORLDY.git cd JORLDY pip install -r requirements.txt # linux apt-get update apt-get -y install libgl1-mesa-glx # for opencv apt-get -y install libglib2.0-0 # for opencv apt-get -y install gifsicle # for gif optimize ``` ### :whale: To use docker (customize if necessary) ``` cd JORLDY docker pull jorldy/jorldy # mac, linux docker run -it --rm --name jorldy -v `pwd`:/JORLDY jorldy/jorldy /bin/bash # windows docker run -it --rm --name jorldy -v %cd%:/JORLDY jorldy/jorldy /bin/bash ``` ### :heavy_plus_sign: To use additional environments __- Atari and Super Mario Bros__ atari and super-mario-bros need to be installed manually due to licensing issues ``` # To use atari(bash) pip install --upgrade gym[atari,accept-rom-license]==0.23.0 # To use atari(zsh) pip install --upgrade 'gym[atari,accept-rom-license]'==0.23.0 # To use super-mario-bros pip install gym-super-mario-bros ``` __- Mujoco__ (Mac and Linux only) __Mujoco is supported in docker.__ However, if you don't use docker, several subprocesses should be done. Please refer to the [mujoco-py github installation](https://github.com/openai/mujoco-py#install-mujoco) ## :rocket: Getting started ``` cd jorldy # Examples: python main.py [run mode] --config [config path] python main.py --config config.dqn.cartpole python main.py --async --config config.ape_x.cartpole # Examples: python main.py [run mode] --config [config path] --[optional parameter key] [parameter value] python main.py --config config.rainbow.atari --env.name breakout python main.py --sync --config config.ppo.cartpole --train.num_workers 8 ``` ## :card_index_dividers: Release | Version | Release Date | Source | Release Note | | :-----: | :--------------: | :--------: | :----------: | | 0.5.0 | April 18, 2022 | [Source](https://github.com/kakaoenterprise/JORLDY/tree/v0.5.0) | [Release Note](https://github.com/kakaoenterprise/JORLDY/releases/tag/v0.5.0) | | 0.4.0 | April 01, 2022 | [Source](https://github.com/kakaoenterprise/JORLDY/tree/v0.4.0) | [Release Note](https://github.com/kakaoenterprise/JORLDY/releases/tag/v0.4.0) | | 0.3.0 | March 10, 2022 | [Source](https://github.com/kakaoenterprise/JORLDY/tree/v0.3.0) | [Release Note](https://github.com/kakaoenterprise/JORLDY/releases/tag/v0.3.0) | | 0.2.0 | January 23, 2022 | [Source](https://github.com/kakaoenterprise/JORLDY/tree/v0.2.0) | [Release Note](https://github.com/kakaoenterprise/JORLDY/releases/tag/v0.2.0) | | 0.1.0 | December 23, 2021 | [Source](https://github.com/kakaoenterprise/JORLDY/tree/v0.1.0) | [Release Note](https://github.com/kakaoenterprise/JORLDY/releases/tag/v0.1.0) | ## :mag: How to - [How to use](./docs/How_to_use.md) - [How to customize con
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Read on GitHubWould you bet a product on this? Bounded 0–100 and slow moving.
matched fp:02782cbb744e8edd, topic:reinforcement-learning, desc:reinforcement learning, readme:reinforcement learning
matched fp:02782cbb744e8edd, topic:pytorch