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20 April 2024
 
  » arxiv » cond-mat/0406425

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Modelling Selforganization and Innovation Processes in Networks
Ingrid Hartmann-Sonntag ; Andrea Scharnhorst ; Werner Ebeling ;
Rating Visitors: 5/5 (1 visitor)
Date 18 Jun 2004
Subject Statistical Mechanics; Disordered Systems and Neural Networks; Physics and Society; Adaptation and Self-Organizing Systems; Populations and Evolution | cond-mat.stat-mech cond-mat.dis-nn nlin.AO physics.soc-ph q-bio.PE
AffiliationHumboldt University Berlin), Andrea Scharnhorst (Royal Netherlands Academy of Arts and Sciences), Werner Ebeling (Humboldt University Berlin
AbstractIn this paper we develop a theory to describe innovation processes in a network of interacting units. We introduce a stochastic picture that allows for the clarification of the role of fluctuations for the survival of innovations in such a non-linear system. We refer to the theory of complex networks and introduce the notion of sensitive networks. Sensitive networks are networks in which the introduction or the removal of a node/vertex dramatically changes the dynamic structure of the system. As an application we consider interaction networks of firms and technologies and describe technological innovation as a specific dynamic process. Random graph theory, percolation, master equation formalism and the theory of birth and death processes are the mathematical instruments used in this paper.
Source arXiv, cond-mat/0406425
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