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MULTI-AGENT: 作品数：981被引量：2487H指数：17; 导出分析报告; 相关领域：自动化与计算机技术更多>>; 相关作者：蒋国瑞黄梯云赵书良杨神化杨乃定更多>>; 相关机构：北京工业大学中南大学北京理工大学武汉理工大学更多>>; 相关期刊：更多>>; 相关基金：国家自然科学基金国家高技术研究发展计划国家教育部博士点基金国家社会科学基金更多>>

Multi-agent deep reinforcement learning based resource management in heterogeneous V2X networks: 《Digital Communications and Networks》2025年第1期182-190,共9页Junhui Zhao Fajin Hu Jiahang Li Yiwen Nie; funded in part by the National Key Research and Development of China Project (2020YFB1807204);in part by National Natural Science Foundation of China (U2001213 and 61971191);in part by the Beijing Natural Science Foundation under Grant L201011;in part by the key project of Natural Science Foundation of Jiangxi Province (20202ACBL202006)。; In Heterogeneous Vehicle-to-Everything Networks(HVNs),multiple users such as vehicles and handheld devices and infrastructure can communicate with each other to obtain more advanced services.However,the increasing num...; 关键词：DATA-DRIVEN Deep reinforcement learning Resource allocation V2X communications

Communication-robust multi-agent learning by adaptable auxiliary multi-agent adversary generation: 《Frontiers of Computer Science》2024年第6期101-117,共17页Lei YUAN Feng CHEN Zongzhang ZHANG Yang YU; the National Key R&D Program of China(2020AAA0107200);the National Natural Science Foundation of China(Grant Nos.61921006,61876119,62276126);the Natural Science Foundation of Jiangsu(BK20221442)。; Communication can promote coordination in cooperative Multi-Agent Reinforcement Learning(MARL).Nowadays,existing works mainly focus on improving the communication efficiency of agents,neglecting that real-world commun...; 关键词：multi-agent communication adversarial training robustness validation reinforcement learning

CoopAI-Route: DRL Empowered Multi-Agent Cooperative System for Efficient QoS-Aware Routing for Network Slicing in Multi-Domain SDN: 《Computer Modeling in Engineering & Sciences》2024年第9期2449-2486,共38页Meignanamoorthi Dhandapani V.Vetriselvi R.Aishwarya; The emergence of beyond 5G networks has the potential for seamless and intelligent connectivity on a global scale.Network slicing is crucial in delivering services for different,demanding vertical applications in this...; 关键词：6G MULTI-DOMAIN MULTI-AGENT ROUTING DRL SDN

Joint UAV trajectory and communication design with heterogeneous multi-agent reinforcement learning: 《Science China(Information Sciences)》2024年第3期221-241,共21页Xuanhan ZHOU Jun XIONG Haitao ZHAO Xiaoran LIU Baoquan REN Xiaochen ZHANG Jibo WEI Hao YIN; supported in part by National Natural Science Foundation of China (Grant Nos.62371462,61931020,62101569,U19B2024);Natural Science Foundation of Hunan Province (Grant No.2022JJ10068);Science and Technology Innovation Program of Hunan Province (Grant No.2022RC1093)。; Unmanned aerial vehicles(UAVs)are recognized as effective means for delivering emergency communication services when terrestrial infrastructures are unavailable.This paper investigates a multiUAV-assisted communicatio...; 关键词：unmanned aerial vehicle(UAV) trajectory design resource allocation multi-agent deep reinforcement learning(MADRL) heterogeneous agents

Multi-Agent Hierarchical Graph Attention Reinforcement Learning for Grid-Aware Energy Management: 《ZTE Communications》2023年第3期11-21,共11页FENG Bingyi FENG Mingxiao WANG Minrui ZHOU Wengang LI Houqiang; supported by National Key R&D Program of China under Grant No.2022ZD0119802;National Natural Science Foundation of China under Grant No.61836011.; The increasing adoption of renewable energy has posed challenges for voltage regulation in power distribution networks.Gridaware energy management,which includes the control of smart inverters and energy management sy...; 关键词：demand-side management graph neural networks multi-agent reinforcement learning voltage regulation

Multi-Agent Deep Reinforcement Learning for Cross-Layer Scheduling in Mobile Ad-Hoc Networks: 《China Communications》2023年第8期78-88,共11页Xinxing Zheng Yu Zhao Joohyun Lee Wei Chen; supported by Institute of Information & communications Technology Planning & Evaluation (IITP) grant funded by the Korea government(MSIT) (No.RS-2022-00155885, Artificial Intelligence Convergence Innovation Human Resources Development (Hanyang University ERICA));supported by the National Natural Science Foundation of China under Grant No. 61971264;the National Natural Science Foundation of China/Research Grants Council Collaborative Research Scheme under Grant No. 62261160390; Due to the fading characteristics of wireless channels and the burstiness of data traffic,how to deal with congestion in Ad-hoc networks with effective algorithms is still open and challenging.In this paper,we focus o...; 关键词：Ad-hoc network cross-layer scheduling multi agent deep reinforcement learning interference elimination power control queue scheduling actorcritic methods markov decision process

A Transmission Design in Dynamic Heterogeneous V2V Networks Through Multi-Agent Deep Reinforcement Learning: 《China Communications》2023年第7期273-289,共17页Nong Qu Chao Wang Zuxing Li Fuqiang Liu; supported in part by the National Natural Science Foundation of China(62171322,62006173);the 2021-2023 China-Serbia Inter-Governmental S&T Cooperation Project(No.6);support of the Sino-German Center of Intelligent Systems,Tongji University;。; In highly dynamic and heterogeneous vehicular communication networks,it is challenging to efficiently utilize network resources and ensure demanding performance requirements of safetyrelated applications.This paper in...; 关键词：V2V communication networks SEQUENTIAL

Multi-User MmWave Beam Tracking via Multi-Agent Deep Q-Learning被引量：1: 《ZTE Communications》2023年第2期53-60,共8页MENG Fan HUANG Yongming LU Zhaohua XIAO Huahua; Beamforming is significant for millimeter wave multi-user massive multi-input multi-output systems.In the meanwhile,the overhead cost of channel state information and beam training is considerable,especially in dynami...; 关键词：multi-agent deep Q-learning centralized training and distributed execution mmWave communication beam tracking scalability

Automatic modelling of urban subsurface with ground-penetrating radar using multi-agent classification method被引量：2: 《Geo-Spatial Information Science》2022年第4期588-599,共12页Tess Xianghuan Luo Pengpeng Yuan Song Zhu; supported by the Shenzhen University[860-000002111308].; The subsurface of urban cities is becoming increasingly congested.In-time records of subsur-face structures are of vital importance for the maintenance and management of urban infrastructure beneath or above the groun...; 关键词：Subsurface modeling ground-penetrating radar computer vision active contour model aggregate channel feature

Cooperative Caching for Scalable Video Coding Using Value-Decomposed Dimensional Networks被引量：2: 《China Communications》2022年第9期146-161,共16页Youjia Chen Yuekai Cai Haifeng Zheng Jinsong Hu Jun Li; supported by the National Natural Science Foundation of China under Grant No.61801119。; Scalable video coding(SVC)has been widely used in video-on-demand(VOD)service,to efficiently satisfy users’different video quality requirements and dynamically adjust video stream to timevariant wireless channels.Und...; 关键词：cooperative caching multi-agent deep reinforcement learning scalable video coding value-decomposition network

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