Work

Multi-Agent Deep Reinforcement Learning for Vehicular Resource Allocation: A Comparison Study of Different Agent Cooperation Levels

Year: 2025

Type: article

Source: IEEE Transactions on Vehicular Technology

DOI: 10.1109/tvt.2025.3582801

Authors: Kang Tan, Ce Zhu

Institution: University of Electronic Science and Technology of China

Language: English

Topic: Vehicular Ad Hoc Networks (VANETs)

Subfield: Electrical and Electronic Engineering

Field: Engineering

Domain: Physical Sciences

SDG: Industry, innovation and infrastructure

Open Access status: closed

OpenAlex ID: W4411600181

FWCI: 1.138

Cites: 32

Cited by: 5

Related to: 10