creators_name: Vigo, Ronaldo creators_id: vigo@ohio.edu type: journalp datestamp: 2012-11-09 17:47:35 lastmod: 2012-11-09 17:47:35 metadata_visibility: show title: Representational information: a new general notion and measure of information ispublished: pub subjects: appl-cog-psy subjects: comp-sci-art-intel subjects: comp-sci-complex-theory subjects: comp-sci-robot subjects: percep-cog-psy subjects: psy-phys full_text_status: public keywords: Representational Information, Concepts, Invariance, Complexity, Information measure, Subjective information abstract: In what follows, we introduce the notion of representational information (information conveyed by sets of dimensionally defined objects about their superset of origin) as well as an original deterministic mathematical framework for its analysis and measurement. The framework, based in part on categorical invariance theory [Vigo, 2009], unifies three key constructsof universal science – invariance, complexity, and information. From this unification we define the amount of information that a well-defined set of objects R carries about its finite superset of origin S, as the rate of change in the structural complexity of S (as determined by its degree of categorical invariance), whenever the objects in R are removed from the set S. The measure captures deterministically the significant role that context and category structure play in determining the relative quantity and quality of subjective information conveyed by particular objects in multi-object stimuli. date: 2011 date_type: published publication: Information Sciences volume: 181 publisher: Elsevier pagerange: 4847-4859 refereed: TRUE referencetext: H.H. Aiken, The Staff of the Computation Laboratory at Harvard University, Synthesis of Electronic Computing and Control Circuits, Harvard University Press, Cambridge, 1951. [2] David Applebaum, Probability and Information, Cambridge University Press, 1996. [3] C.M. 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[Journal (Paginated)] document_url: http://cogprints.org/7961/1/Vigo_Information_Sciences.pdf