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Simulating innovation: Comparing models of collective knowledge, technological evolution and emergent innovation networks

Watts, C and Gilbert, N (2014) Simulating innovation: Comparing models of collective knowledge, technological evolution and emergent innovation networks Advances in Intelligent Systems and Computing, 229 AI. pp. 189-200.

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Abstract

Computer simulation models have been proposed as a tool for understanding innovation, including models of organisational learning, technological evolution, knowledge dynamics and the emergence of innovation networks. By representing micro-level interactions they provide insight into the mechanisms by which are generated various stylised facts about innovation phenomena. This paper summarises work carried out as part of the SIMIAN project and to be covered in more detail in a forthcoming book. A critical review of existing innovation- related models is performed. Models compared include a model of collective learning in networks [1], a model of technological evolution based around percolation on a grid [2, 3], a model of technological evolution that uses Boolean logic gate designs [4], the SKIN model [5], a model of emergent innovation networks [6], and the hypercycles model of economic production [7]. The models are compared for the ways they represent knowledge and/or technologies, how novelty enters the system, the degree to which they represent open-ended systems, their use of networks, landscapes and other pre-defined structures, and the patterns that emerge from their operations, including networks and scale-free frequency distributions. Suggestions are then made as to what features future innovation models might contain. © Springer-Verlag Berlin Heidelberg 2014.

Item Type: Article
Divisions : Faculty of Arts and Social Sciences > Department of Sociology
Authors :
AuthorsEmailORCID
Watts, CUNSPECIFIEDUNSPECIFIED
Gilbert, NUNSPECIFIEDUNSPECIFIED
Date : 2014
Identification Number : 10.1007/978-3-642-39829-2_17
Additional Information : The original publication is available at http://www.springerlink.com
Depositing User : Symplectic Elements
Date Deposited : 09 Sep 2014 09:05
Last Modified : 02 Oct 2014 01:33
URI: http://epubs.surrey.ac.uk/id/eprint/805906

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