Identifying Emergent Dynamical Structures in Network Models

  • Marco Villani
  • Stefano Benedettini
  • Andrea Roli
  • David Lane
  • Irene Poli
  • Roberto Serra
Part of the Smart Innovation, Systems and Technologies book series (SIST, volume 26)

Abstract

The identification of emergent structures in dynamical systems is a major challenge in complex systems science. In particular, the formation of intermediate-level dynamical structures is of particular interest for what concerns biological as well as artificial network models. In this work, we present a new technique aimed at identifying clusters of nodes in a network that behave in a coherent and coordinated way and that loosely interact with the remainder of the system. This method is based on an extension of a measure introduced for detecting clusters in biological neural networks. Even if our results are still preliminary, we have evidence for showing that our approach is able to identify these “emerging things” in some artificial network models and that it is way more powerful than usual measures based on statistical correlation. This method will make it possible to identify mesolevel dynamical structures in network models in general, from biological to social networks.

Keywords

Dynamical systems emergent dynamical structures cluster index boolean networks emergent properties 

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Copyright information

© Springer International Publishing Switzerland 2014

Authors and Affiliations

  • Marco Villani
    • 1
    • 2
  • Stefano Benedettini
    • 1
  • Andrea Roli
    • 1
    • 3
  • David Lane
    • 1
    • 4
  • Irene Poli
    • 1
    • 5
  • Roberto Serra
    • 1
    • 2
  1. 1.European Centre for Living TechnologyVeneziaItaly
  2. 2.Dept. of Physics, Informatics and MathematicsUniversity of Modena e Reggio EmiliaModenaItaly
  3. 3.DISI Alma Mater Studiorum University of Bologna Campus of CesenaCesenaItaly
  4. 4.Dept. of Communication and EconomicsUniversity of Modena e Reggio EmiliaReggio emiliaItaly
  5. 5.Department of Environmental Sciences, Informatics and StatisticsUniversity Ca’FoscariVeniceItaly

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