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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 | Affiliation: | Humboldt University Berlin), Andrea Scharnhorst (Royal Netherlands Academy of Arts and Sciences), Werner Ebeling (Humboldt University Berlin | 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. | Source: | arXiv, cond-mat/0406425 | Services: | Forum | Review | PDF | Favorites |
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