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JORLDY (Beta)

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Hello WoRLd!!:hand: Join Our Reinforcement Learning framework for Developing Yours (JORLDY) is an open-source Reinforcement Learning (RL) framework provided by KakaoEnterprise. It is named after Jordy, one of the Kakao 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.

🔥 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
  • Benchmark of the algorithms is conducted in many RL environment

✔️ Tested

Python Windows Mac Linux
3.8
3.7
Windows Server 2022 macOS Big Sur 11
macOS Catalina 10.15
Ubuntu 20.04
Ubuntu 18.04

⬇️ 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

🐳 To use docker

(customize if necessary)

cd JORLDY

# mac, linux
docker build -t jorldy -f ./docker/Dockerfile .
docker run -it --rm --name jorldy -v `pwd`:/JORLDY jorldy /bin/bash

# windows
docker build -t jorldy -f .\docker\Dockerfile .
docker run -it --rm --name jorldy -v %cd%:/JORLDY jorldy /bin/bash

➕ 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
pip install --upgrade gym[atari,accept-rom-license]
 
# 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

🚀 Getting started

cd jorldy

# Examples: python [script name] --config [config path]
python single_train.py --config config.dqn.cartpole
python single_train.py --config config.rainbow.atari --env.name assault

# Examples: python [script name] --config [config path] --[optional parameter key] [parameter value]
python single_train.py --config config.dqn.cartpole --agent.batch_size 64
python sync_distributed_train.py --config config.ppo.cartpole --train.num_workers 8 

🗂️ Release

Version Release Date Source Release Note
0.1.0 December 23, 2021 Source Release Note
0.0.3 November 23, 2021 Source Release Note
0.0.2 November 06, 2021 Source Release Note
0.0.1 November 03, 2021 Source Release Note

🔍 How to

📄 Documentation

👥 Contributors

📫 Contact: [email protected]

contributors

©️ License

Apache License 2.0

🚫 Disclaimer

Installing in JORLDY and/or utilizing algorithms or environments not provided KEP may involve a use of third party’s intellectual property. It is advisable that a user obtain licenses or permissions from the right holder(s), if necessary, or take any other necessary measures to avoid infringement or misappropriation of third party’s intellectual property rights.

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