论文标题
统一的分布环境
Unified Distributed Environment
论文作者
论文摘要
我们提出了统一的分布环境（UDE），这是一种用于强化学习研究的环境虚拟化工具包。 UDE旨在集成在任何模拟平台上建立的环境，例如凉亭，团结，虚幻和OpenAI健身房。通过环境虚拟化，UDE可以使环境在远程计算机上执行，同时仍保持统一接口。 UDE接口旨在默认支持多代理。通过环境虚拟化及其界面设计，可以在多台机器中培训代理策略，以供多个代理环境进行培训。此外，UDE支持与现有的主要RL工具包的集成，以便研究人员利用收益。本文讨论了UDE及其设计决策的组成部分。
We propose Unified Distributed Environment (UDE), an environment virtualization toolkit for reinforcement learning research. UDE is designed to integrate environments built on any simulation platform such as Gazebo, Unity, Unreal, and OpenAI Gym. Through environment virtualization, UDE enables offloading the environment for execution on a remote machine while still maintaining a unified interface. The UDE interface is designed to support multi-agent by default. With environment virtualization and its interface design, the agent policies can be trained in multiple machines for a multi-agent environment. Furthermore, UDE supports integration with existing major RL toolkits for researchers to leverage the benefits. This paper discusses the components of UDE and its design decisions.
