z-logo
open-access-imgOpen Access
Unified Formalization of «Natural» Classification, «Natural» Concepts, and Consciousness as Integrated Information by Giulio Tononi1
Author(s) -
Evgenii Vityaev
Publication year - 2015
Publication title -
procedia computer science
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.334
H-Index - 76
ISSN - 1877-0509
DOI - 10.1016/j.procs.2015.12.191
Subject(s) - natural (archaeology) , computer science , property (philosophy) , representation (politics) , set (abstract data type) , basis (linear algebra) , natural kind , artificial intelligence , natural number , consciousness , theoretical computer science , natural language , natural language processing , epistemology , mathematics , programming language , philosophy , physics , geometry , archaeology , discrete mathematics , politics , political science , acoustics , law , history , identity (music)
The paper shows that the basis for the construction of “natural” classifications, “natural” concepts and integrated information is the same property of the objects of the external world - the high correlation of attributes describing the objects of “natural” classes. The hypothesis that the information processes of the brain and mind tuned in the course of evolution to extract highly correlated structure attributes of “natural” objects by forming “natural” concepts of the objects was suggested. This hypothesis is justified by references to a number of famous works. Besides, the original mathematical model is proposed, which formalizes the “natural” classifications, “natural” concepts and the integrated information by G. Tononi, based on a mathematical representation of the system, closed upon itself by causal relationships that form a certain “resonance” of mutual predictions of highly correlated set of attributes of objects of “natural” classes. The results of computer modeling of building “natural” classes and concepts for coded digits are introduced

The content you want is available to Zendy users.

Already have an account? Click here to sign in.
Having issues? You can contact us here
Accelerating Research

Address

John Eccles House
Robert Robinson Avenue,
Oxford Science Park, Oxford
OX4 4GP, United Kingdom