Federated Multiagent Actor–Critic Learning Task Offloading in Intelligent Logistics-Reference-Cited by-同舟云学术

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Federated Multiagent Actor–Critic Learning Task Offloading in Intelligent Logistics

Published:2023-07-01 Issue:13 Volume:10 Page:11696-11707
ISSN:2327-4662
Container-title:IEEE Internet of Things Journal
language:
Short-container-title:IEEE Internet Things J.

Author:

Li Qiqi¹,Cui Yaping²^ORCID,Song Tao³,Zheng Linjiang¹^ORCID

Affiliation:

1. College of Computer Science, Chongqing University, Chongqing, China

2. School of Communication and Information Engineering, Chongqing University of Posts and Telecommunications, Chongqing, China

3. Industrial Internet and IoT Research Institute, China Academy of Information and Communications Technology, Beijing, China

Funder

National Key Research and Development Program of China

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/ielx7/6488907/10159464/10044215.pdf?arnumber=10044215

Reference35 articles.

1. SMART Logistics Chain

2. Applications of the Internet of Things (IoT) in Smart Logistics: A Comprehensive Survey

3. Industry 4.0 implications in logistics: an overview

4. Smart logistics based on the internet of things technology: an overview

5. Cooperative Vehicular Networking: A Survey

Cited by 3 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Comprehensive survey on reinforcement learning-based task offloading techniques in aerial edge computing;Internet of Things;2024-12

2. Resource allocation optimization for effective vehicle network communications using multi-agent deep reinforcement learning;Journal of Dynamics and Games;2024

3. Fine-grained Task Scheduling Based on Graph Neural Network and Federated Learning in Vehicle Edge Computing;2023 IEEE 29th International Conference on Parallel and Distributed Systems (ICPADS);2023-12-17

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