Dynamic Collectives and Their Collective Dynamics

2005 ◽  
pp. 300-315 ◽  
Author(s):  
Antony Galton
Keyword(s):  
Collective Dynamics

Emergence of learning in computer-supported, large-scale collective dynamics

2007 ◽  
Author(s):  
Manu Kapur ◽  
David Hung ◽  
Michael Jacobson ◽  
John Voiklis ◽  
Charles K. Kinzer ◽  
...  
Keyword(s):  
Large Scale ◽  
Collective Dynamics

Stability and bifurcation of collective dynamics in phase oscillator populations with general coupling

2021 ◽  
Vol 103 (3) ◽  
Author(s):  
Can Xu ◽  
Xuan Wang ◽  
Zhigang Zheng ◽  
Zongkai Cai
Keyword(s):  
Phase Oscillator ◽  
Collective Dynamics ◽  
Stability And Bifurcation

scholarly journals Cognitive Profiling of Nodes in 6G through Multiplex Social Network and Evolutionary Collective Dynamics

2021 ◽  
Vol 13 (5) ◽  
pp. 135
Author(s):  
Marialisa Scatá ◽  
Barbara Attanasio ◽  
Aurelio La Corte
Keyword(s):  
Social Network ◽  
Complex Systems ◽  
Communication Networks ◽  
Digital Health ◽  
Evolutionary Game ◽  
Mathematical Representation ◽  
Collective Dynamics ◽  
Self Organized ◽  
Learning And Cognition ◽  
Application Fields

Complex systems are fully described by the connectedness of their elements studying how these develop a collective behavior, interacting with each other following their inner features, and the structure and dynamics of the entire system. The forthcoming 6G will attempt to rewrite the communication networks’ perspective, focusing on a radical revolution in the way entities and technologies are conceived, integrated and used. This will lead to innovative approaches with the aim of providing new directions to deal with future network challenges posed by the upcoming 6G, thus the complex systems could become an enabling set of tools and methods to design a self-organized, resilient and cognitive network, suitable for many application fields, such as digital health or smart city living scenarios. Here, we propose a complex profiling approach of heterogeneous nodes belonging to the network with the goal of including the multiplex social network as a mathematical representation that enables us to consider multiple types of interactions, the collective dynamics of diffusion and competition, through social contagion and evolutionary game theory, and the mesoscale organization in communities to drive learning and cognition. Through a framework, we detail the step by step modeling approach and show and discuss our findings, applying it to a real dataset, by demonstrating how the proposed model allows us to detect deeply complex knowable roles of nodes.

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