MeFi: Mean Field Reinforcement Learning for Cooperative Routing in Wireless Sensor Network
Author:
Affiliation:
1. School of Information and Communication Engineering, University of Electronic Science and Technology of China, Chengdu, China
2. School of Electrical Engineering and Telecommunications, University of New South Wales, Sydney, NSW, Australia
Funder
Special Project for Research and Development in Key areas of Guangdong Province
NSFC Fund
Open Research Projects of Zhejiang Lab
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Subject
Computer Networks and Communications,Computer Science Applications,Hardware and Architecture,Information Systems,Signal Processing
Link
http://xplorestaging.ieee.org/ielx7/6488907/10375273/10164652.pdf?arnumber=10164652
Reference33 articles.
1. Internet of Things in the 5G Era: Enablers, Architecture, and Business Models
2. A Survey on Urban Traffic Management System Using Wireless Sensor Networks
3. An inland Wireless Sensor Network system for monitoring seismic activity
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1. Multi-Agent Deep Reinforcement Learning for Packet Routing in Tactical Mobile Sensor Networks;IEEE Transactions on Network and Service Management;2024-04
2. Duty Cycle Scheduling in Wireless Sensor Networks Using an Exploratory Strategy-Directed MADDPG Algorithm;International Journal of Sensors and Sensor Networks;2024-02-28
3. Reinforcement-Learning-Based Routing and Resource Management for Internet of Things Environments: Theoretical Perspective and Challenges;Sensors;2023-10-06
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