MULTI-AGENT

作品数：981被引量：2487H指数：17
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相关领域：自动化与计算机技术更多>>
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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>>
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Development of Multi-Agent-Based Indoor 3D Reconstruction
《Computers, Materials & Continua》2024年第10期161-181,共21页Hoi Chuen Cheng Frederick Ziyang Hong Babar Hussain Yiru Wang Chik Patrick Yue 
supported by Bright Dream Robotics and the HKUSTBDR Joint Research Institute Funding Scheme under Project HBJRI-FTP-005(Automated 3D Reconstruction using Robot-mounted 360-Degree Camera with Visible Light Positioning Technology for Building Information Modelling Applications,OKT22EG06).
Large-scale indoor 3D reconstruction with multiple robots faces challenges in core enabling technologies.This work contributes to a framework addressing localization,coordination,and vision processing for multi-agent ...
关键词：Multi-agent system multi-robot human collaboration visible light communication visible light positioning 3D reconstruction reinforcement learning multi-agent path finding 
Research on Maneuver Decision-Making of Multi-Agent Adversarial Game in a Random Interference Environment
《Computers, Materials & Continua》2024年第10期1879-1903,共25页Shiguang Hu Le Ru Bo Lu Zhenhua Wang Xiaolin Zhao Wenfei Wang Hailong Xi 
The strategy evolution process of game players is highly uncertain due to random emergent situations and other external disturbances.This paper investigates the issue of strategy interaction and behavioral decision-ma...
关键词：Behavior decision-making stochastic evolutionary game nonlinear mathematical modeling MULTI-AGENT MANEUVER 
Service Function Chain Deployment Algorithm Based on Multi-Agent Deep Reinforcement Learning
《Computers, Materials & Continua》2024年第9期4875-4893,共19页Wanwei Huang Qiancheng Zhang Tao Liu YaoliXu Dalei Zhang 
The financial support fromthe Major Science and Technology Programs inHenan Province(Grant No.241100210100);National Natural Science Foundation of China(Grant No.62102372);Henan Provincial Department of Science and Technology Research Project(Grant No.242102211068);Henan Provincial Department of Science and Technology Research Project(Grant No.232102210078);the Stabilization Support Program of The Shenzhen Science and Technology Innovation Commission(Grant No.20231130110921001);the Key Scientific Research Project of Higher Education Institutions of Henan Province(Grant No.24A520042)is acknowledged.
Aiming at the rapid growth of network services,which leads to the problems of long service request processing time and high deployment cost in the deployment of network function virtualization service function chain(S...
关键词：Network function virtualization service function chain Markov decision process multi-agent reinforcement learning 
An Empirical Study on Google Research Football Multi-agent Scenarios
《Machine Intelligence Research》2024年第3期549-570,共22页Yan Song He Jiang Zheng Tian Haifeng Zhang Yingping Zhang Jiangcheng Zhu Zonghong Dai Weinan Zhang Jun Wang 
supported by the National Natural Science Foundation of China(No.62206289).
Few multi-agent reinforcement learning (MARL) researches on Google research football (GRF) focus on the 11-vs-11 multi-agent full-game scenario and to the best of our knowledge, no open benchmark on this scenario has ...
关键词：Multi-agent reinforcement learning(RL) distributed RL system population-based training reward shaping game theory 
UAV-Assisted Dynamic Avatar Task Migration for Vehicular Metaverse Services: A Multi-Agent Deep Reinforcement Learning Approach被引量：1
《IEEE/CAA Journal of Automatica Sinica》2024年第2期430-445,共16页Jiawen Kang Junlong Chen Minrui Xu Zehui Xiong Yutao Jiao Luchao Han Dusit Niyato Yongju Tong Shengli Xie 
supported in part by NSFC (62102099, U22A2054, 62101594);in part by the Pearl River Talent Recruitment Program (2021QN02S643);Guangzhou Basic Research Program (2023A04J1699);in part by the National Research Foundation, Singapore;Infocomm Media Development Authority under its Future Communications Research Development Programme;DSO National Laboratories under the AI Singapore Programme under AISG Award No AISG2-RP-2020-019;Energy Research Test-Bed and Industry Partnership Funding Initiative, Energy Grid (EG) 2.0 programme;DesCartes and the Campus for Research Excellence and Technological Enterprise (CREATE) programme;MOE Tier 1 under Grant RG87/22;in part by the Singapore University of Technology and Design (SUTD) (SRG-ISTD-2021- 165);in part by the SUTD-ZJU IDEA Grant SUTD-ZJU (VP) 202102;in part by the Ministry of Education, Singapore, through its SUTD Kickstarter Initiative (SKI 20210204)。
Avatars, as promising digital representations and service assistants of users in Metaverses, can enable drivers and passengers to immerse themselves in 3D virtual services and spaces of UAV-assisted vehicular Metavers...
关键词：AVATAR blockchain metaverses multi-agent deep reinforcement learning transformer UAVS 
A multi-agent deep reinforcement learning approach for solving the multi-depot vehicle routing problem
《Journal of Management Analytics》2023年第3期493-515,共23页Ali Arishi Krishna Krishnan 
The multi-depot vehicle routing problem(MDVRP)is one of the most essential and useful variants of the traditional vehicle routing problem(VRP)in supply chain management(SCM)and logistics studies.Many supply chains(SC)...
关键词：artificial intelligence supply chain management combinatorial optimization multi-depot vehicle routing problem multi-agent deep reinforcement learning 
Offline Pre-trained Multi-agent Decision Transformer被引量：3
《Machine Intelligence Research》2023年第2期233-248,共16页Linghui Meng Muning Wen Chenyang Le Xiyun Li Dengpeng Xing Weinan Zhang Ying Wen Haifeng Zhang Jun Wang Yaodong Yang Bo Xu 
Linghui Meng was supported in part by the Strategic Priority Research Program of the Chinese Academy of Sciences(No.XDA27030300);Haifeng Zhang was supported in part by the National Natural Science Foundation of China(No.62206289).
Offline reinforcement learning leverages previously collected offline datasets to learn optimal policies with no necessity to access the real environment.Such a paradigm is also desirable for multi-agent reinforcement...
关键词：Pre-training model multi-agent reinforcement learning(MARL) decision making TRANSFORMER offline reinforcement learning 
Load Balancing Based on Multi-Agent Framework to Enhance Cloud Environment
《Computers, Materials & Continua》2023年第2期3015-3028,共14页Shrouk H.Hessen Hatem M.Abdul-kader Ayman E.Khedr Rashed K.Salem 
According to the advances in users’service requirements,physical hardware accessibility,and speed of resource delivery,Cloud Computing(CC)is an essential technology to be used in many fields.Moreover,the Internet of ...
关键词：Cloud computing IoT multi-agent system load balancing algorithm server utilities 
UAV Frequency-based Crowdsensing Using Grouping Multi-agent Deep Reinforcement Learning
《计算机科学》2023年第2期57-68,共12页Cui ZHANG En WANG Funing YANG Yong jian YANG Nan JIANG 
supported by the Innovation Capacity Construction Project of Jilin Development and Reform Commission(2020C017-2);Science and Technology Development Plan Project of Jilin Province(20210201082GX)。
Mobile CrowdSensing(MCS)is a promising sensing paradigm that recruits users to cooperatively perform sensing tasks.Recently,unmanned aerial vehicles(UAVs)as the powerful sensing devices are used to replace user partic...
关键词：UAV Crowdsensing Frequency coverage Grouping multi-agent deep reinforcement learning 
Formal Modeling of Self-Adaptive Resource Scheduling in Cloud
《Computers, Materials & Continua》2023年第1期1183-1197,共15页Atif Ishaq Khan Syed Asad Raza Kazmi Awais Qasim 
A self-adaptive resource provisioning on demand is a critical factor in cloud computing.The selection of accurate amount of resources at run time is not easy due to dynamic nature of requests.Therefore,a self-adaptive...
关键词：Formal modeling MULTI-AGENT SELF-ADAPTIVE cloud computing 
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