Order, organization, and randomness: on the mathematical formulation of life.
Life increasingly is understood in terms of information. I consider two attempts to formulate life in terms of mathematical information theory. G. J. Chaitin's proposes to define life in terms of the relation between organization and algorithmic compressibility in biological information. More recent...
| Publicado en: | Synthese Vol. 204; no. 6; pp. 1 - 18 |
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| Formato: | Artículo |
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Springer Nature
Dec2024
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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=180988711&site=ehost-live header: @attributes: shortDbName: hlh uiTerm: 180988711 longDbName: Humanities International Complete uiTag: AN controlInfo: bkinfo: jinfo: jid: 00397857 4LI jtl: Synthese issn: 00397857 maglogo: N pubinfo: dt: Dec2024 vid: 204 iid: 6 pid: 237 pub: Springer Nature artinfo: ui: 180988711 10.1007/s11229-024-04806-6 ppf: 1 ppct: 17 formats: fmt: – @attributes: type: T – @attributes: type: P size: 1MB tig: atl: Order, organization, and randomness: on the mathematical formulation of life. aug: au: Cosgrove, Joseph K. affil: https://ror.org/00rxpqe74 Philosophy Department, Providence College, 1 Cunningham Square, 02918, Providence, RI, USA Worcester, USA su: Information measurement Algorithmic randomness Information theory Compressibility Organization sug: subj: Information measurement Algorithmic randomness Information theory Compressibility Organization ab: Life increasingly is understood in terms of information. I consider two attempts to formulate life in terms of mathematical information theory. G. J. Chaitin's proposes to define life in terms of the relation between organization and algorithmic compressibility in biological information. More recently, William Dembski, Winston Ewart, and Robert J. Marks suggest that Dembski's notion of specified complexity can be mathematically expressed in information-theoretic terms through the concept of algorithmic specified complexity. The mathematical approaches are similar and in both cases essentially dependent on the concept of randomness deficiency in algorithmic information theory: to subtract out the degree of randomness from an informational measure, yielding a remainder of organization (Chatin) or specified complexity (Dembski, Ewart, and Marks). I argue that these attempts must fail due the information-theoretic indistinguishability of organization and randomness. The failure is instructive, however, because it illustrates the inability of mathematical information theory to register biological organization. pubtype: Academic Journal doctype: Article src: R language: English refInfo: copyright: @attributes: flag: Y custom: Synthese is a copyright of Springer, 2024. All Rights Reserved. item: Synthese holder: Springer Nature dt: @attributes: year: 2024 holdings: @attributes: islocal: N |
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