Disagreement Behavior Analysis of Signed Networks. Questo articolo non è disponibile.Disagreement Behavior Analysis of Signed Networks

This book investigates the disagreement behavior analysis problems for signed networks in the presence of both cooperative and antagonistic interactions among agents. Owing to the existing antagonistic interactions, signed networks exhibit a variety of disagreement behaviors subject to different topology conditions, especially in comparison with commonly considered unsigned networks involving only cooperative interactions among agents. Since signed networks are generally adopted to describe the dynamics of some practical network systems, they have attracted much attention in many areas, such as biology, sociology, economics, and politics. By focusing on agents with the first-order linear dynamics, the book establishes the systematic behavior analysis frameworks for signed networks, under which diverse disagreement behaviors have been disclosed, including both convergence and fluctuation behaviors, regardless of static or dynamic network topologies. In particular, a class of dynamic signed networks has been introduced, together with the associated dynamic distributed controller design and disagreement behavior analysis of agents. This book is intended for undergraduate and graduate students, engineers, and researchers who are interested in control of network systems, multi-agent systems, social networks, and so on.

Mingjun Du received the M.S. degree in mathematics and the Ph.D. degree in control theory and control engineering from Beihang University (BUAA), Beijing, China, in 2015 and 2020, respectively. He is currently with the School of Information and Automation Engineering, Qilu University of Technology (Shandong Academy of Science), Shandong, China. His current research interests include multi-agent systems and social opinion dynamics. 

  

Yuxin Wu received the B.S. degree in automation from North China Electric Power University, Beijing, China, in June 2017, and the M.S. degree in control theory and control engineering from Beihang University (BUAA), Beijing, China, in January 2020. She is currently working towards her Ph.D. degree in Beihang University (BUAA). Her research interests include multi-agent systems, data-driven control, and iterative learning control.