English

Modelling Selforganization and Innovation Processes in Networks

Statistical Mechanics 2007-05-23 v1 Disordered Systems and Neural Networks Adaptation and Self-Organizing Systems Physics and Society Populations and Evolution

Abstract

In 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.

Keywords

Cite

@article{arxiv.cond-mat/0406425,
  title  = {Modelling Selforganization and Innovation Processes in Networks},
  author = {Ingrid Hartmann-Sonntag and Andrea Scharnhorst and Werner Ebeling},
  journal= {arXiv preprint arXiv:cond-mat/0406425},
  year   = {2007}
}

Comments

59 pages LaTeX, 15 figures (in part LaTeX generated), Springer LNP style

R2 v1 2026-07-22T11:04:30.266Z