Open AccessA Theory of Heuristic Reasoning About Uncertainty
Author(s) -
Cohen Paul R.,
Grinberg Milton R.
Publication year - 1983
Publication title -
ai magazine
Language(s) - English
Resource type - Book series
SCImago Journal Rank - 0.597
H-Index - 79
eISSN - 2371-9621
pISSN - 0738-4602
ISBN - 0-929280-01-6
DOI - 10.1609/aimag.v4i2.393
Subject(s) - certainty , heuristic , representation (politics) , computer science , artificial intelligence , dempster–shafer theory , bayesian probability , mathematical economics , management science , mathematics , epistemology , engineering , philosophy , politics , political science , law
This article describes a theory of reasoning about uncertainty, based on a representation of states of certainty called endorsements The theory of endorsements is an alternative to numerical methods for reasoning about uncertainty, such as subjective Bayesian methods (Shortliffe and Buchanan, 1975; Duda, Hart, and Nilsson, 1976) and the Shafer‐Dempster theory (Shafer, 1976). The fundamental concern with numerical representations of certainty is that they hide the reasoning that produces them and thus limit one's reasoning about uncertainty While numbers are easy to propagate over inferences, what the numbers mean is unclear The theory of endorsements provides a richer representation of the factors that affect certainty and supports multiple strategies for dealing with uncertainty.