公开(公告)号：US20210081787A1

公开(公告)日：2021-03-18

申请号：US17015269

申请日：2020-09-09

Applicant: Beijing University of Posts and Telecommunications

Inventor： Qi QI ,  Haifeng SUN ,  Jing WANG ,  Lingxin ZHANG ,  Jingyu WANG ,  Jianxin LIAO

IPC: G06N3/08 ,  G06N3/04

Abstract: Disclosed are a method and apparatus for task scheduling based on deep reinforcement learning and a device. The method comprises: obtaining multiple target subtasks to be scheduled; building target state data corresponding to the multiple target subtasks, wherein the target state data comprises a first set, a second set, a third set, and a fourth set; inputting the target state data into a pre-trained task scheduling model, to obtain a scheduling result of each target subtask; wherein, the scheduling result of each target subtask comprises a probability that the target subtask is scheduled to each target node; for each target subtask, determining a target node to which the target subtask is to be scheduled based on the scheduling result of the target subtask, and scheduling the target subtask to the determined target node.