Artificial Intelligence Dialects of the Bayesian Belief Revision Language
17 Pages Posted: 31 Oct 2008
Date Written: September 1989
Abstract
Rule-based expert systems must deal with uncertain data,subjective expert opinions, and inaccurate decision rules. Computer scientistsand psychologists have proposed and implemented a number of belief languages widely used in applied systems, and their normative validity is clearly an important question, both on practical as well on theoretical grounds. Several well-know belief languages are reviewed, and both previous work and new insights into their Bayesian interpretations are presented. Inparticular, the authors focus on three alternative belief-update models thecertainty factors calculus, Dempster-Shafer simple support functions, andthe descriptive contrast/inertia model. Important "dialects� of these languages are shown to be isomorphic to each other and to a special case ofBayesian inference. Parts of this analysis were carried out by other authors; these results were extended and consolidated using an analytic technique designed to study the kinship of belief languages in general.
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