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Empirical Modeling and Information Semantics

Fulltext:


Authors:

Gordana Dodig-Crnkovic

Note:

http://www.springerlink.com/content/45454q54j3151304

Research group:

Artificial Intelligence and Intelligent Systems

Publication Type:

Journal article

Venue:

Mind & Society

Publisher:

Springer

Abstract

Abstract This paper investigates the relationship between reality and model, information and truth. It will argue that meaningful data need not be true in order to constitute information. Information to which truth-value cannot be ascribed, partially true information or even false information can lead to an interesting outcome such as technological innovation or scientific breakthrough. In the research process, during the transition between two theoretical frameworks, there is a dynamic mixture of old and new concepts in which truth is not well defined. Instead of veridicity, correctness of a model and its appropriateness within a context are commonly required. Despite empirical models being in general only truthlike, they are nevertheless capable of producing results from which conclusions can be drawn and adequate decisions made. Keywords Modeling Æ Information Æ Semantics Æ Validation and verification Æ Veridicity Æ Truthlikeness

Bibtex

@article{Dodig-Crnkovic1114,
author = {Gordana Dodig-Crnkovic},
title = {Empirical Modeling and Information Semantics},
note = {http://www.springerlink.com/content/45454q54j3151304},
volume = {7},
number = { Issue 2},
month = {November},
year = {2008},
journal = {Mind {\&} Society},
publisher = {Springer},
url = {http://www.es.mdu.se/publications/1114-}
}