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Dresden 2014 – scientific programme

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SOE: Fachverband Physik sozio-ökonomischer Systeme

SOE 10: Networks, From Topology to Dynamics I (joint with DY and BP)

SOE 10.4: Talk

Tuesday, April 1, 2014, 15:45–16:00, GÖR 226

Automatic discovery of plausible network modelsTelmo Menezes1,2 and •Camille Roth11Centre Marc Bloch Berlin, CNRS — 2Centre d'Analyse et de Mathématique Sociales, CNRS/EHESS

A methodology is proposed to discover plausible network generators for complex networks. Generators are defined as computer programs that define local morphogenetic behaviors. We employ a machine learning technique inspired by biological Darwinism to look for generators that produce synthetic networks which match a number of metrics on target real networks. We use a number of metrics that capture both global and fine-grained structural characteristics of networks. Remarkably, when applied on networks stemming from prototypical models of the Erdös-Rényi or Barabási-Albert sort, our approach generally discovers the exact original generator. Empirical validation of our methodology is then presented in the form of a number of plausible generators for a series of five real networks, including a simple brain and a social network.

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