Multi-Agent Deep Reinforcement Learning for Distributed Resource Management in Wirelessly Powered Communication Networks

被引：0
|
作者：
Hwang, Sangwon [1 ]
Kim, Hanjin [2 ]
Lee, Hoon [3 ]
Lee, Inkyu [1 ]
机构：
[1] School of Electrical Engineering, Korea University, Seoul, Korea, Republic of
[2] Samsung Research, Samsung Electronics Co. Ltd., Seoul, Korea, Republic of
[3] Department of Information and Communications Engineering, Pukyong National University, Busan, Korea, Republic of
来源：
IEEE Transactions on Vehicular Technology | 2020年 / 69卷 / 11期
关键词：
Deep learning - Multi agent systems - Resource allocation - Telecommunication networks;
D O I：
暂无
中图分类号：
学科分类号：
摘要：
引用
收藏
页码：14055 / 14060
相关论文
共 50 条
  • [41] Multi-Agent Reinforcement Learning for Edge Resource Management with Reconstructed Environment
    Miao, Weiwei
    Zeng, Zeng
    Zhang, Mingxuan
    Quan, Siping
    Zhang, Zhen
    Li, Shihao
    Zhang, Li
    Sun, Qi
    19TH IEEE INTERNATIONAL SYMPOSIUM ON PARALLEL AND DISTRIBUTED PROCESSING WITH APPLICATIONS (ISPA/BDCLOUD/SOCIALCOM/SUSTAINCOM 2021), 2021, : 1729 - 1736
  • [42] Deep Reinforcement Learning Agent for Negotiation in Multi-Agent Cooperative Distributed Predictive Control
    Aponte-Rengifo, Oscar
    Vega, Pastora
    Francisco, Mario
    APPLIED SCIENCES-BASEL, 2023, 13 (04):
  • [43] Distributed Deep Reinforcement Learning: A Survey and a Multi-player Multi-agent Learning Toolbox
    Yin, Qiyue
    Yu, Tongtong
    Shen, Shengqi
    Yang, Jun
    Zhao, Meijing
    Ni, Wancheng
    Huang, Kaiqi
    Liang, Bin
    Wang, Liang
    MACHINE INTELLIGENCE RESEARCH, 2024, 21 (03) : 411 - 430
  • [44] Distributed Deep Reinforcement Learning: A Survey and a Multi-player Multi-agent Learning Toolbox
    Qiyue Yin
    Tongtong Yu
    Shengqi Shen
    Jun Yang
    Meijing Zhao
    Wancheng Ni
    Kaiqi Huang
    Bin Liang
    Liang Wang
    Machine Intelligence Research, 2024, 21 : 411 - 430
  • [45] Deep Reinforcement Learning for Multi-Agent Power Control in Heterogeneous Networks
    Zhang, Lin
    Liang, Ying-Chang
    IEEE TRANSACTIONS ON WIRELESS COMMUNICATIONS, 2021, 20 (04) : 2551 - 2564
  • [46] Routing with Graph Convolutional Networks and Multi-Agent Deep Reinforcement Learning
    Bhavanasi, Sai Shreyas
    Pappone, Lorenzo
    Esposito, Flavio
    2022 IEEE CONFERENCE ON NETWORK FUNCTION VIRTUALIZATION AND SOFTWARE DEFINED NETWORKS (IEEE NFV-SDN), 2022, : 72 - 77
  • [47] Scaling Collaborative Space Networks with Deep Multi-Agent Reinforcement Learning
    Ma, Ricky
    Hernandez, Gabe
    Hernandez, Carrie
    2023 IEEE COGNITIVE COMMUNICATIONS FOR AEROSPACE APPLICATIONS WORKSHOP, CCAAW, 2023,
  • [48] Multi-Agent Deep Reinforcement Learning for Coordinated Multipoint in Mobile Networks
    Schneider, Stefan
    Karl, Holger
    Khalili, Ramin
    Hecker, Artur
    IEEE TRANSACTIONS ON NETWORK AND SERVICE MANAGEMENT, 2024, 21 (01): : 908 - 924
  • [49] Learning structured communication for multi-agent reinforcement learning
    Sheng, Junjie
    Wang, Xiangfeng
    Jin, Bo
    Yan, Junchi
    Li, Wenhao
    Chang, Tsung-Hui
    Wang, Jun
    Zha, Hongyuan
    AUTONOMOUS AGENTS AND MULTI-AGENT SYSTEMS, 2022, 36 (02)
  • [50] Learning structured communication for multi-agent reinforcement learning
    Junjie Sheng
    Xiangfeng Wang
    Bo Jin
    Junchi Yan
    Wenhao Li
    Tsung-Hui Chang
    Jun Wang
    Hongyuan Zha
    Autonomous Agents and Multi-Agent Systems, 2022, 36
12345