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dc.contributor.authorHodgson, G.M.
dc.contributor.authorKnudsen, T.
dc.date.accessioned2011-03-07T14:36:49Z
dc.date.available2011-03-07T14:36:49Z
dc.date.issued2010
dc.identifier.citationHodgson , G M & Knudsen , T 2010 , ' Generative replication and the evolution of complexity ' , Journal of Economic Behavior and Organization , vol. 75 , no. 1 , pp. 12-24 . https://doi.org/10.1016/j.jebo.2010.03.008
dc.identifier.issn0167-2681
dc.identifier.otherPURE: 81946
dc.identifier.otherPURE UUID: 2c35e172-f5fb-4826-85d2-6afc04f0bbb7
dc.identifier.otherdspace: 2299/5438
dc.identifier.otherScopus: 77953538538
dc.identifier.urihttp://hdl.handle.net/2299/5438
dc.descriptionOriginal article can be found at: http://www.sciencedirect.com/ Copyright Elsevier
dc.description.abstractThis paper identifies generative replication as a form of replication which has the potential to enhance complexity in social and biological evolution, including the wondrous complexity in the biological world, and complex social institutions such as human language and business corporations. We draw inspiration from the literature on self-reproducing automata to clarify the notion of information transfer in replication processes. To enhance complexity, developmental instructions must be part of the information that is transmitted in replication. In addition to the established triple conditions of causality, similarity and information transfer, a generative replicator involves a conditional generative mechanism that can use signals from an environment and create developmental instructions. We develop a simple model, a one-dimensional linear automaton that is consistent with our four proposed conditions for a generative replicator. We show that evolution within this model will indeed approach maximal complexity, but only if our four proposed conditions are not violated. © 2010 Elsevier B.V.en
dc.format.extent13
dc.language.isoeng
dc.relation.ispartofJournal of Economic Behavior and Organization
dc.subjectreplication
dc.subjectreplicators
dc.subjectinformation
dc.subjectcomplexity
dc.subjectautomata
dc.titleGenerative replication and the evolution of complexityen
dc.contributor.institutionGroup for Research in Organisational Evolution
dc.contributor.institutionHertfordshire Business School
dc.contributor.institutionSocial Sciences, Arts & Humanities Research Institute
dc.contributor.institutionCentre for Research on Management, Economy and Society
dc.contributor.institutionDepartment of Accounting, Finance and Economics
dc.description.statusPeer reviewed
dc.identifier.urlhttp://www.scopus.com/inward/record.url?scp=77953538538&partnerID=8YFLogxK
rioxxterms.versionofrecordhttps://doi.org/10.1016/j.jebo.2010.03.008
rioxxterms.typeJournal Article/Review
herts.preservation.rarelyaccessedtrue


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