TY - JOUR
T1 - The Confluence of Networks, Games, and Learning a Game-Theoretic Framework for Multiagent Decision Making Over Networks
AU - Li, Tao
AU - Peng, Guanze
AU - Zhu, Quanyan
AU - Basar, Tamer
N1 - Publisher Copyright:
© 1991-2012 IEEE.
PY - 2022/8/1
Y1 - 2022/8/1
N2 - 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].
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].
UR - http://www.scopus.com/inward/record.url?scp=85135335827&partnerID=8YFLogxK
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U2 - 10.1109/MCS.2022.3171478
DO - 10.1109/MCS.2022.3171478
M3 - Review article
AN - SCOPUS:85135335827
SN - 1066-033X
VL - 42
SP - 35
EP - 67
JO - IEEE Control Systems
JF - IEEE Control Systems
IS - 4
ER -