title: Representational information: a new general notion and measure  of information
creator: Vigo, Professor Ronaldo
subject: Applied Cognitive Psychology
subject: Artificial Intelligence
subject: Complexity Theory
subject: Robotics
subject: Perceptual Cognitive Psychology
subject: Psychophysics
description: 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.
publisher: Elsevier 
date: 2011
type: Journal (Paginated)
type: PeerReviewed
format: application/pdf
identifier: http://cogprints.org/7961/1/Vigo_Information_Sciences.pdf
identifier:   Vigo, Professor Ronaldo  (2011) Representational information: a new general notion and measure of information.  [Journal (Paginated)]     
relation: http://cogprints.org/7961/