Communication resource allocation method in vehicular networks based on federated multi-agent deep reinforcement learning

Qingli Liu; Yongjie Ma

doi:10.1038/s41598-025-15982-x

ScienceGate Book Chapters

JOURNAL ARTICLE

Communication resource allocation method in vehicular networks based on federated multi-agent deep reinforcement learning

Qingli Liu Yongjie Ma

Year: 2025 Journal: Scientific Reports Vol: 15 (1)Pages: 30866-30866 Publisher: Nature Portfolio

DOI: 10.1038/s41598-025-15982-x

Get Full-Text PDF Get Analytical Report

Keywords:

Reinforcement learning Computer science Resource allocation Reinforcement Resource (disambiguation) Artificial intelligence Computer network Distributed computing Engineering

Metrics

Cited By

9.64

FWCI (Field Weighted Citation Impact)

Refs

0.97

Citation Normalized Percentile

Is in top 1%

Is in top 10%

Citation History

Topics

Privacy-Preserving Technologies in Data

Physical Sciences → Computer Science → Artificial Intelligence

Vehicular Ad Hoc Networks (VANETs)

Physical Sciences → Engineering → Electrical and Electronic Engineering

Advanced Data and IoT Technologies

Physical Sciences → Engineering → Electrical and Electronic Engineering

Communication resource allocation method in vehicular networks based on federated multi-agent deep reinforcement learning

Metrics

Citation History

Topics

Related Documents

Resource Allocation in Vehicular Networks Based on Federated Multi-Agent Reinforcement Learning

Resource allocation strategy for vehicular communication networks based on multi-agent deep reinforcement learning

Multi-agent reinforcement learning based resource allocation for vehicular networks

Heterogeneous Resource Allocation in LEO Networks: A Federated Multi-Agent Deep Reinforcement Learning Method

Multi-Agent Deep Reinforcement Learning for Channel Resource Allocation in Vehicular Networks