云南高校图书馆联盟文献共享服务平台- MULTI-AGENT

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>>

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

Automatic Generation Control in a Distributed Power Grid Based on Multi-step Reinforcement Learning: 《Protection and Control of Modern Power Systems》2024年第4期39-50,共12页Wenmeng Zhao Tuo Zeng Zhihong Liu Lihui Xie Lei Xi Hui Ma; supported by the National Natural Sci-ence Foundation of China(No.52277108);Guangdong Provincial Department of Science and Technology(No.2022A0505020015).; The increasing use of renewable energy in the power system results in strong stochastic disturbances and degrades the control performance of the distributed power grids.In this paper,a novel multi-agent collaborative ...; 关键词：Automatic generation control Dyna framework distributed power grid MULTI-AGENT mod-el-based reinforcement learning

Multi-Agent Collaborative Task Planning with Uncertain Task Requirements: 《Journal of Beijing Institute of Technology》2024年第5期361-373,共13页Jia Zhang Zexuan Jin Qichen Dong; supported by the National Natural Science Foundation of China(No.61903036)。; In response to the uncertainty of information of the injured in post disaster situations,considering constraints such as random chance and the quantity of rescue resource,the split deliv-ery vehicle routing problem wi...; 关键词：multi-agent collaboration task planning vehicle routing problem stochastic demands

A Task Offloading Strategy Based on Multi-Agent Deep Reinforcement Learning for Offshore Wind Farm Scenarios: 《Computers, Materials & Continua》2024年第10期985-1008,共24页Zeshuang Song Xiao Wang Qing Wu Yanting Tao Linghua Xu Yaohua Yin Jianguo Yan; supported in part by the National Natural Science Foundation of China under grant 61861007;the Guizhou Province Science and Technology Planning Project ZK[2021]303;the Guizhou Province Science Technology Support Plan under grant[2022]264,[2023]096,[2023]409 and[2023]412;the Science Technology Project of POWERCHINA Guizhou Engineering Co.,Ltd.(DJ-ZDXM-2022-44);the Project of POWERCHINA Guiyang Engineering Corporation Limited(YJ2022-12).; This research is the first application of Unmanned Aerial Vehicles(UAVs)equipped with Multi-access Edge Computing(MEC)servers to offshore wind farms,providing a new task offloading solution to address the challenge of...; 关键词：Offshore wind MEC task offloading MADRL AGA-DDPG

Regional Multi-Agent Cooperative Reinforcement Learning for City-Level Traffic Grid Signal Control: 《IEEE/CAA Journal of Automatica Sinica》2024年第9期1987-1998,共12页Yisha Li Ya Zhang Xinde Li Changyin Sun; supported by the National Science and Technology Major Project (2021ZD0112702);the National Natural Science Foundation (NNSF)of China (62373100,62233003);the Natural Science Foundation of Jiangsu Province of China (BK20202006)。; This article studies the effective traffic signal control problem of multiple intersections in a city-level traffic system.A novel regional multi-agent cooperative reinforcement learning algorithm called RegionSTLight...; 关键词：Human-machine cooperation mixed domain attention mechanism multi-agent reinforcement learning spatio-temporal feature traffic signal control

Game-theoretic multi-agent motion planning in a mixed environment: 《Control Theory and Technology》2024年第3期379-393,共15页Xiaoxue Zhang Lihua Xie; supported by the A*STAR under its"RIE2025 IAF-PP Advanced ROS2-native Platform Technologies for Cross sectorial Robotics Adoption(M21K1a0104)"programme.; The motion planning problem for multi-agent systems becomes particularly challenging when humans or human-controlled robots are present in a mixed environment.To address this challenge,this paper presents an interacti...; 关键词：Motion planning Differential potential game Multi-agent systems Constrained potential game

Multi-Objective Loosely Synchronized Search for Multi-Objective Multi-Agent Path Finding with Asynchronous Actions: 《Journal of Shanghai Jiaotong university(Science)》2024年第4期667-677,共11页DU Haikuo GUO Zhengyu ZHANG Lulu CAI Yunze; Aeronautical Science Foundation of China(No.20220001057001)。; In recent years,the path planning for multi-agent technology has gradually matured,and has made breakthrough progress.The main difficulties in path planning for multi-agent are large state space,long algorithm running...; 关键词：multi-agent path finding multi-objective path planning asynchronous action loosely synchronous search

Multi-agent policy transfer via task relationship modeling: 《Science China(Information Sciences)》2024年第8期98-110,共13页Rongjun QIN Feng CHEN Tonghan WANG Lei YUAN Xiaoran WU Yipeng KANG Zongzhang ZHANG Chongjie ZHANG Yang YU; supported in part by National Key Research and Development Program of China(Grant No.2020AAA0107200);National Natural Science Foundation of China(Grant Nos.61876119,61921006);Natural Science Foundation of Jiangsu(GrantNo.BK20221442)。; Team adaptation to new cooperative tasks is a hallmark of human intelligence,which has yet to be fully realized in learning agents.Previous studies on multi-agent transfer learning have accommodated teams of different...; 关键词：multi-agent reinforcement learning cooperative transfer learning task relationship modeling multi-agent policy reuse multi-agent multi-task learning

Distributed Heterogeneous Multi-Agent Optimization with Stochastic Sub-Gradient: 《Journal of Systems Science & Complexity》2024年第4期1470-1487,共18页HU Haokun MO Lipo CAO Xianbing; supported by the National Natural Science Foundation of China under Grant No.61973329;National Key Technology R&D Program of China under Grant No.2021YFD2100605;Project of Beijing Municipal University Teacher Team Construction Support Plan under Grant No.BPHR20220104。; This paper studies the optimization problem of heterogeneous networks under a timevarying topology.Each agent only accesses to one local objective function,which is nonsmooth.An improved algorithm with noisy measureme...; 关键词：Communication noises distributed stochastic optimization heterogeneous networks subgradient measurement noises

Multi-Agent Path Planning Method Based on Improved Deep Q-Network in Dynamic Environments: 《Journal of Shanghai Jiaotong university(Science)》2024年第4期601-612,共12页LI Shuyi LI Minzhe JING Zhongliang; National Natural Science Foundation of China(Nos.61673262 and 50779033);National GF Basic Research Program(No.JCKY2021110B134);Fundamental Research Funds for the Central Universities。; The multi-agent path planning problem presents significant challenges in dynamic environments,primarily due to the ever-changing positions of obstacles and the complex interactions between agents’actions.These factor...; 关键词：MULTI-AGENT path planning deep reinforcement learning deep Q-network

高级检索 检索式检索

时间限定

期刊范围

学科限定全选

高级检索 检索式检索

时间限定

期刊范围

学科限定全选

MULTI-AGENT

检索结果分析

下载全文

高级检索检索式检索

时间限定

期刊范围

学科限定全选

高级检索 检索式检索

时间限定

期刊范围

学科限定全选

MULTI-AGENT

检索结果分析

下载全文

用户登录

高级检索检索式检索