Self-organized complexity and Coherent Infomax from the viewpoint of Jaynes’s probability theory

  • This paper discusses concepts of self-organized complexity and the theory of Coherent Infomax in the light of Jaynes’s probability theory. Coherent Infomax, shows, in principle, how adaptively self-organized complexity can be preserved and improved by using probabilistic inference that is context-sensitive. It argues that neural systems do this by combining local reliability with flexible, holistic, context-sensitivity. Jaynes argued that the logic of probabilistic inference shows it to be based upon Bayesian and Maximum Entropy methods or special cases of them. He presented his probability theory as the logic of science; here it is considered as the logic of life. It is concluded that the theory of Coherent Infomax specifies a general objective for probabilistic inference, and that contextual interactions in neural systems perform functions required of the scientist within Jaynes’s theory.

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Metadaten
Author:William A. Phillips
URN:urn:nbn:de:hebis:30:3-253122
DOI:https://doi.org/10.3390/info3010001
ISSN:2078-2489
Parent Title (English):Information
Publisher:Molecular Diversity Preservation International (MDPI)
Place of publication:Basel
Document Type:Article
Language:English
Date of Publication (online):2012/06/27
Date of first Publication:2012/01/04
Publishing Institution:Universitätsbibliothek Johann Christian Senckenberg
Release Date:2012/06/27
Tag:Coherent Infomax; Jaynes; complexity; context-sensitivity; coordination; information; neural computation; probabilistic inference; probability theory; self-organization
Volume:3.2012
Issue:1
Page Number:15
First Page:1
Last Page:15
HeBIS-PPN:357590635
Institutes:Wissenschaftliche Zentren und koordinierte Programme / Frankfurt Institute for Advanced Studies (FIAS)
Dewey Decimal Classification:0 Informatik, Informationswissenschaft, allgemeine Werke / 00 Informatik, Wissen, Systeme / 004 Datenverarbeitung; Informatik
Sammlungen:Universitätspublikationen
Licence (German):License LogoCreative Commons - Namensnennung 3.0