Mob Control: Models of Threshold Collective Behavior [electronic resource] /
By: Breer, Vladimir V [author.].
Contributor(s): Novikov, Dmitry A [author.] | Rogatkin, Andrey D [author.] | SpringerLink (Online service).
Series: Studies in Systems, Decision and Control: 85Publisher: Cham : Springer International Publishing : Imprint: Springer, 2017Edition: 1st ed. 2017.Description: VIII, 134 p. 29 illus., 13 illus. in color. | Binding - Card Paper |.Content type: text Media type: computer Carrier type: online resourceISBN: 9783319518657.Subject(s): Computer Engineering | Artificial intelligence | Control engineering | Computational Intelligence | Complex SystemsDDC classification: 006.3 Online resources: Click here to access eBook in Springer Nature platform. (Within Campus only.) In: Springer Nature eBookSummary: This book presents mathematical models of mob control with threshold (conformity) collective decision-making of the agents. Based on the results of analysis of the interconnection between the micro- and macromodels of active network structures, it considers the static (deterministic, stochastic and game-theoretic) and dynamic (discrete- and continuous-time) models of mob control, and highlights models of informational confrontation. Many of the results are applicable not only to mob control problems, but also to control problems arising in social groups, online social networks, etc. Aimed at researchers and practitioners, it is also a valuable resource for undergraduate and postgraduate students as well as doctoral candidates specializing in the field of collective behavior modeling.This book presents mathematical models of mob control with threshold (conformity) collective decision-making of the agents. Based on the results of analysis of the interconnection between the micro- and macromodels of active network structures, it considers the static (deterministic, stochastic and game-theoretic) and dynamic (discrete- and continuous-time) models of mob control, and highlights models of informational confrontation. Many of the results are applicable not only to mob control problems, but also to control problems arising in social groups, online social networks, etc. Aimed at researchers and practitioners, it is also a valuable resource for undergraduate and postgraduate students as well as doctoral candidates specializing in the field of collective behavior modeling.
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