论文标题
Jorldy：一个完全可自定义的开源框架，用于增强学习
JORLDY: a fully customizable open source framework for reinforcement learning
论文作者
论文摘要
最近，在学术和工业领域都对强化学习（RL）进行了积极研究。但是，只有少数RL框架是针对想要学习RL的研究人员或学生开发的。作为回应，我们提出了一个开源RL框架，“加入我们的增强学习框架为开发自己的框架”（Jorldy）。 Jorldy提供了20多种使用Pytorch实现的广泛使用的RL算法。此外，Jorldy支持多个RL环境，包括OpenAI体育馆，Unity ML-Agent，Mujoco，Super Mario Bros和Procgen。此外，可以自定义算法组件，例如代理，网络，环境，以便用户可以轻松修改和附加算法组件。我们预计Jorldy将支持各种RL研究，并进一步推进RL领域。 Jorldy的源代码在以下github上提供：https：//github.com/kakaoenterprise/jorldy
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
