The Confluence of Networks, Games, and Learning a Game-Theoretic Framework for Multiagent Decision Making Over Networks

Tao LI; Guanze PENG; Quanyan ZHU; Tamer BASAR

doi:10.1109/MCS.2022.3171478

The Confluence of Networks, Games, and Learning a Game-Theoretic Framework for Multiagent Decision Making Over Networks

Tao LI^*
, Guanze PENG
, Quanyan ZHU
, Tamer BASAR

^*Corresponding author for this work

Research output: Journal Publications and Reviews › RGC 21 - Publication in refereed journal › peer-review

45 Citations (Scopus)

Abstract

Multiagent decision making over networks has recently attracted an exponentially growing number of researchers from the systems and control community. The area has gained increasing momentum in engineering, social sciences, economics, urban science, and artificial intelligence as it serves as a prevalent framework for studying large and complex systems and has been widely applied to many problems, such as social networks analysis [1], [2], smart grid management [3], [4], wireless and communication networks [5]-[7], cybersecurity [8]-[10], critical infrastructures [11]-[13], and cyberphysical systems [14]-[16]. © 2022 IEEE.

Original language	English
Pages (from-to)	35-67
Journal	IEEE Control Systems
Volume	42
Issue number	4
Online published	19 Jul 2022
DOIs	https://doi.org/10.1109/MCS.2022.3171478
Publication status	Published - Aug 2022
Externally published	Yes

Funding

This work is partially supported by grants SES-1541164, ECCS-1847056, CNS-2027884, and BCS-2122060 from the National Science Foundation, grant 20-19829 from DOE-NE, and grant W911NF-19-1-0041 from the Army Research Office.

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abstract = "Multiagent decision making over networks has recently attracted an exponentially growing number of researchers from the systems and control community. The area has gained increasing momentum in engineering, social sciences, economics, urban science, and artificial intelligence as it serves as a prevalent framework for studying large and complex systems and has been widely applied to many problems, such as social networks analysis [1], [2], smart grid management [3], [4], wireless and communication networks [5]-[7], cybersecurity [8]-[10], critical infrastructures [11]-[13], and cyberphysical systems [14]-[16]. {\textcopyright} 2022 IEEE.",

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AB - Multiagent decision making over networks has recently attracted an exponentially growing number of researchers from the systems and control community. The area has gained increasing momentum in engineering, social sciences, economics, urban science, and artificial intelligence as it serves as a prevalent framework for studying large and complex systems and has been widely applied to many problems, such as social networks analysis [1], [2], smart grid management [3], [4], wireless and communication networks [5]-[7], cybersecurity [8]-[10], critical infrastructures [11]-[13], and cyberphysical systems [14]-[16]. © 2022 IEEE.

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EP - 67

JO - IEEE Control Systems

JF - IEEE Control Systems

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The Confluence of Networks, Games, and Learning a Game-Theoretic Framework for Multiagent Decision Making Over Networks

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