Title: Deep reinforcement learning multi-robot cooperative scheduling based on service entity network

Authors: Xueguang Jin; Chengrui Wu; Yan Yan; Yingli Liu

Addresses: College of Cyberspace Security, Changzhou College of Information Technology, Changzhou Productivity Development Centre, Changzhou Vocational Institute of Engineering, Changzhou University, Changzhou, Jiangsu, China ' College of Cyberspace Security, Changzhou College of Information Technology, Changzhou Productivity Development Centre, Changzhou Vocational Institute of Engineering, Changzhou University, Changzhou, Jiangsu, China ' College of Cyberspace Security, Changzhou College of Information Technology, Changzhou Productivity Development Centre, Changzhou Vocational Institute of Engineering, Changzhou University, Changzhou, Jiangsu, China ' College of Cyberspace Security, Changzhou College of Information Technology, Changzhou Productivity Development Centre, Changzhou Vocational Institute of Engineering, Changzhou University, Changzhou, Jiangsu, China

Abstract: Multi-robot is increasingly deployed with the development of automatics in agriculture, industry and warehousing logistics. With the help of CPS virtualisation technology, services or tasks can be decomposed into a network with capability or function entity nodes and edges connecting nodes. In this paper, the service entity network is extended with the human, robot and IT resources as a task decomposed network with public entities, private entities and links. Based on the service entity network virtualisation architecture, it is possible to form a global service entity network corresponding to the correlated tasks. Meanwhile, deep reinforcement learning multi-robot cooperative scheduling based on a service entity network framework is studied, which makes it possible to jointly optimise the deployment of multi-robot tasks with multi-service entity networks. The results show that the model based on the artificial intelligence virtualisation architecture achieves a better performance.

Keywords: service entity network; virtualisation technology; multi-robot cooperative scheduling.

DOI: 10.1504/IJWMC.2025.148064

International Journal of Wireless and Mobile Computing, 2025 Vol.29 No.2, pp.142 - 149

Received: 28 Aug 2022
Received in revised form: 15 Dec 2022
Accepted: 04 Jan 2023
Published online: 25 Aug 2025 *

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