Mean-Field-Aided Multiagent Reinforcement Learning for Resource Allocation in Vehicular Networks-Reference-Cited by-同舟云学术

Mean-Field-Aided Multiagent Reinforcement Learning for Resource Allocation in Vehicular Networks

Published:2023-02-01 Issue:3 Volume:10 Page:2667-2679
ISSN:2327-4662
Container-title:IEEE Internet of Things Journal
language:
Short-container-title:IEEE Internet Things J.

Author:

Zhang Hengxi¹,Lu Chengyue¹,Tang Huaze¹^ORCID,Wei Xiaoli¹,Liang Le²^ORCID,Cheng Ling³^ORCID,Ding Wenbo¹^ORCID,Han Zhu⁴^ORCID

Affiliation:

1. Tsinghua–Berkeley Shenzhen Institute, Tsinghua Shenzhen International Graduate School, Tsinghua University, Shenzhen, China

2. National Mobile Communications Research Laboratory, Frontiers Science Center for Mobile Information Communication and Security, Southeast University, Nanjing, China

3. School of Electrical and Information Engineering, University of the Witwatersrand, Johannesburg, South Africa

4. Department of Electrical and Computer Engineering, University of Houston, Houston, TX, USA

Funder

Fundamental Research Funds for the Central Universities

Natural Science Foundation of Jiangsu Province

National Research Foundation of South Africa

NSF

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Computer Networks and Communications,Computer Science Applications,Hardware and Architecture,Information Systems,Signal Processing

Link

https://ieeexplore.ieee.org/ielam/6488907/10024910/9919273-aam.pdf

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4. Dynamic Computation Offloading for Mobile Cloud Computing: A Stochastic Game-Theoretic Approach

5. Stochastic Game for Wireless Network Virtualization