Networked Signal and Information Processing: Learning by multiagent systems

被引:6
作者
Vlaski, Stefan [1 ,2 ]
Kar, Soummya [3 ]
Sayed, Ali H. [4 ,5 ,6 ,7 ]
Moura, Jose M. F. [8 ,9 ,10 ,11 ,12 ]
机构
[1] Imperial Coll, London SW7 2AZ, England
[2] Ecole Polytech Fed Lausanne, Adapt Syst Lab, Lausanne, Switzerland
[3] Princeton Univ, Elect Engn Dept, Princeton, NJ USA
[4] Ecole Polytech Fed Lausanne, CH-1015 Lausanne, Switzerland
[5] Univ Calif Los Angeles, Elect Engn, Los Angeles, CA USA
[6] US Natl Acad Engn, Washington, DC USA
[7] World Acad Sci, Trieste, Italy
[8] Carnegie Mellon Univ, Pittsburgh, PA 15213 USA
[9] Amer Assoc Advancement Sci, Washington, DC USA
[10] Natl Acad Inventors, Tampa, FL USA
[11] Portugal Acad Sci, Lisbon, Portugal
[12] Natl Acad Engn, New Delhi, India
关键词
Privacy; Protocols; Network topology; Scalability; Signal processing algorithms; Information processing; Robustness; DISTRIBUTED CONSENSUS ALGORITHMS; PART I; SENSOR NETWORKS; ADAPTIVE NETWORKS; LARGE-SCALE; OPTIMIZATION; DIFFUSION; CONVERGENCE; PERFORMANCE; STABILITY;
D O I
10.1109/MSP.2023.3267896
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
This article reviews significant advances in networked signal and information processing (SIP), which have enabled in the last 25 years extending decision making and inference, optimization, control, and learning to the increasingly ubiquitous environments of distributed agents. As these interacting agents cooperate, new collective behaviors emerge from local decisions and actions. Moreover, and significantly, theory and applications show that networked agents, through cooperation and sharing, are able to match the performance of cloud or federated solutions while offering the potential for improved privacy, increased resilience, and conserved resources. A longer version of this manuscript, with examples and illustrative applications, is available at https://arxiv.org/abs/2210.13767.
引用
收藏
页码:92 / 105
页数:14
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