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

Z. Liu; Yi‐Fei Deng

doi:10.1016/j.vehcom.2025.100895

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JOURNAL ARTICLE

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

Z. Liu Yi‐Fei Deng

Year: 2025 Journal: Vehicular Communications Vol: 53 Pages: 100895-100895 Publisher: Elsevier BV

DOI: 10.1016/j.vehcom.2025.100895

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Keywords:

Computer science Reinforcement learning Resource allocation Vehicular ad hoc network Artificial intelligence Operations research Distributed computing Computer network Telecommunications Wireless ad hoc network Wireless

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Topics

Vehicular Ad Hoc Networks (VANETs)

Physical Sciences → Engineering → Electrical and Electronic Engineering

Transportation and Mobility Innovations

Physical Sciences → Engineering → Automotive Engineering

Advanced MIMO Systems Optimization

Physical Sciences → Engineering → Electrical and Electronic Engineering

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

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Citation History

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