The machine as data: a computational view of emergence and definability.
Turing's (Proceedings of the London Mathematical Society 42:230-265, ) paper on computable numbers has played its role in underpinning different perspectives on the world of information. On the one hand, it encourages a digital ontology, with a perceived flatness of computational structure comprehen...
| Publicado en: | Synthese Vol. 192; no. 7; pp. 1955 - 1989 |
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| Formato: | Artículo |
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Springer Nature
Jul2015
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=hlh&AN=109574756&site=ehost-live header: @attributes: shortDbName: hlh uiTerm: 109574756 longDbName: Humanities International Complete uiTag: AN controlInfo: bkinfo: jinfo: jid: 00397857 4LI jtl: Synthese issn: 00397857 maglogo: N pubinfo: dt: Jul2015 vid: 192 iid: 7 pid: 237 pub: Springer Nature artinfo: ui: 109574756 10.1007/s11229-015-0803-4 ppf: 1955 ppct: 34 formats: fmt: @attributes: type: P size: 539KB tig: atl: The machine as data: a computational view of emergence and definability. aug: au: Cooper, S. affil: School of Mathematics, University of Leeds, Leeds LS2 9JT UK su: Turing machines Computational number theory Turing, Alan Mathison, 1912-1954 Von Neumann, John, 1903-1957 Artificial intelligence Russell, Bertrand, 1872-1970 Computational learning theory sug: subj: Turing machines Computational number theory Turing, Alan Mathison, 1912-1954 Von Neumann, John, 1903-1957 Artificial intelligence Russell, Bertrand, 1872-1970 Computational learning theory keyword: Embodiment Emergence Higher order computation Incomputability Turing definability Universality ab: Turing's (Proceedings of the London Mathematical Society 42:230-265, ) paper on computable numbers has played its role in underpinning different perspectives on the world of information. On the one hand, it encourages a digital ontology, with a perceived flatness of computational structure comprehensively hosting causality at the physical level and beyond. On the other (the main point of Turing's paper), it can give an insight into the way in which higher order information arises and leads to loss of computational control-while demonstrating how the control can be re-established, in special circumstances, via suitable type reductions. We examine the classical computational framework more closely than is usual, drawing out lessons for the wider application of information-theoretical approaches to characterizing the real world. The problem which arises across a range of contexts is the characterizing of the balance of power between the complexity of informational structure (with emergence, chaos, randomness and 'big data' prominently on the scene) and the means available (simulation, codes, statistical sampling, human intuition, semantic constructs) to bring this information back into the computational fold. We proceed via appropriate mathematical modelling to a more coherent view of the computational structure of information, relevant to a wide spectrum of areas of investigation. pubtype: Academic Journal doctype: Article src: R language: English refInfo: copyright: @attributes: flag: Y custom: Synthese is a copyright of Springer, 2015. All Rights Reserved. item: Synthese holder: Springer Nature dt: @attributes: year: 2015 holdings: @attributes: islocal: N |
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