English

JORLDY: a fully customizable open source framework for reinforcement learning

Machine Learning 2022-04-12 v1 Artificial Intelligence

Abstract

Recently, Reinforcement Learning (RL) has been actively researched in both academic and industrial fields. However, there exist only a few RL frameworks which are developed for researchers or students who want to study RL. In response, we propose an open-source RL framework "Join Our Reinforcement Learning framework for Developing Yours" (JORLDY). JORLDY provides more than 20 widely used RL algorithms which are implemented with Pytorch. Also, JORLDY supports multiple RL environments which include OpenAI gym, Unity ML-Agents, Mujoco, Super Mario Bros and Procgen. Moreover, the algorithmic components such as agent, network, environment can be freely customized, so that the users can easily modify and append algorithmic components. We expect that JORLDY will support various RL research and contribute further advance the field of RL. The source code of JORLDY is provided on the following Github: https://github.com/kakaoenterprise/JORLDY

Keywords

Cite

@article{arxiv.2204.04892,
  title  = {JORLDY: a fully customizable open source framework for reinforcement learning},
  author = {Kyushik Min and Hyunho Lee and Kwansu Shin and Taehak Lee and Hojoon Lee and Jinwon Choi and Sungho Son},
  journal= {arXiv preprint arXiv:2204.04892},
  year   = {2022}
}

Comments

12 pages, 6 figures

R2 v1 2026-06-24T10:44:05.502Z