A novel simulator called VMAgent is introduced to help RL researchers better explore new methods, especially for virtual machine scheduling. VMAgent is inspired by practical virtual machine (VM) scheduling tasks and provides an efficient simulation platform that can reflect the real situations of cloud computing. Three scenarios (fading, recovering, and expansion) are concluded from practical cloud computing and corresponds to many reinforcement learning challenges (high dimensional state and action spaces, high non-stationarity, and life-long demand). VMAgent provides flexible configurations for RL researchers to design their customized scheduling environments considering different problem features. From the VM scheduling perspective, VMAgent also helps to explore better learning-based scheduling solutions.

翻译：引入了名为 VMAGent 的新型模拟器,以帮助RL 研究人员更好地探索新方法,特别是虚拟机器调度。 VMAGent 受实用虚拟机器(VM)调度任务的启发,并提供了一个能反映云计算真实情况的高效模拟平台。三种情景( 淡化、恢复和扩展)由实用云计算得出,与许多强化学习挑战( 高维状态和动作空间、 高非静止性和终身需求)相对应。 VMAGent 为RL 研究人员设计考虑到不同问题的定制排程环境提供了灵活的配置。 从 VM 排程角度看, VMAGent 也帮助探索更好的基于学习的排程解决方案。