Content
Frontiers of Information Technology & Electronic Engineering >> 2022, Volume 23, Issue 1 doi: 10.1631/FITEE.2100331
Multi-agent deep reinforcement learning for end–edge orchestrated resource allocation in industrial wireless networks
Affiliation(s): State Key Laboratory of Robotics, Shenyang Institute of Automation, Chinese Academy of Sciences, Shenyang 110016, China; Key Laboratory of Networked Control Systems, Chinese Academy of Sciences, Shenyang 110016, China; Institutes for Robotics and Intelligent Manufacturing, Chinese Academy of Sciences, Shenyang 110169, China; University of Chinese Academy of Sciences, Beijing 100049, China; less
Abstract
Keywords
Multi-agent deep reinforcement learning ; End–edge orchestrated ; Industrial wireless networks ; Delay ; Energy consumption
Content