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March 12, 2026IEICE Transactions on Fundamentals of Electronics Communications and Computer Sciences

M-MADDPG: Research on Cooperative Optimization of Task Offloading and Network Resources in Vehicular Networks

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Authors

QXQ. F. XuCWChengyu WuAZAo ZHAN

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Overview

This letter introduces M-MADDPG, optimizing resource allocation in vehicular networks, suggesting enhanced performance.

Key Points

  • The research aims to develop an algorithm for optimizing task offloading and network resources in vehicular networks.
  • Introduced M-MADDPG, a multi-agent deep reinforcement learning algorithm.
  • Utilized multi-head attention for feature extraction and agent cooperation.
  • Conducted extensive simulations to evaluate performance.
  • M-MADDPG outperforms traditional methods in throughput.
  • Demonstrated improved adaptability in dynamic environments.
  • Showed robustness and scalability for future vehicular networks.

Cite This Study

Xu et al. (2026) studied this question.

synapsesocial.com/papers/69b25aab96eeacc4fcec8acehttps://doi.org/10.1587/transfun.2025eal2099
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