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Multi-agent deep reinforcement learning based resource management in heterogeneous V2X networks

Junhui Zhao Fajin Hu Jiahang Li Yiwen Nie

Digital Communications and Networks2025，Vol.11Issue(1)：P.182-190,9.

Digital Communications and Networks2025，Vol.11Issue(1)：P.182-190,9.DOI:10.1016/j.dcan.2023.06.003

Multi-agent deep reinforcement learning based resource management in heterogeneous V2X networks

Junhui Zhao ¹Fajin Hu ²Jiahang Li ³Yiwen Nie²

作者信息

1. School of Electronic and Information Engineering,Beijing Jiaotong University,Beijing 100044,China School of Information Engineering,East China Jiaotong University,Nanchang 330013,China
2. School of Electronic and Information Engineering,Beijing Jiaotong University,Beijing 100044,China
3. School of Electronic and Information Engineering,Beijing Jiaotong University,Beijing 100044,China Research Institute of China United Network Communications Group Co.,Ltd.,Beijing,100048,China
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摘要

关键词

Data-driven/Deep reinforcement learning/Resource allocation/V2X communications

分类

交通工程

引用本文复制引用

Junhui Zhao,Fajin Hu,Jiahang Li,Yiwen Nie..Multi-agent deep reinforcement learning based resource management in heterogeneous V2X networks[J].Digital Communications and Networks,2025,11(1):P.182-190,9.

基金项目

funded in part by the National Key Research and Development of China Project (2020YFB1807204) （2020YFB1807204）

in part by National Natural Science Foundation of China (U2001213 and 61971191) （U2001213 and 61971191）

in part by the Beijing Natural Science Foundation under Grant L201011 （）

in part by the key project of Natural Science Foundation of Jiangxi Province (20202ACBL202006)。（20202ACBL202006）

Digital Communications and Networks

ISSN：2468-5925

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