Accession Number : ADA324260
Title : Bayesian Knowledge-Bases.
Descriptive Note : Technical rept.,
Corporate Author : AIR FORCE INST OF TECH WRIGHT-PATTERSON AFB OH SCHOOL OF ENGINEERING
Personal Author(s) : Santos, Eugene, Jr. ; Santos, Eugene
PDF Url : ADA324260
Report Date : 12 AUG 1996
Pagination or Media Count : 22
Abstract : Abstract Managing uncertainty in complex domains requires a flexible and semantically sound knowledge representation. This is especially important during the initial knowledge engineering and subsequent maintenance of the knowledge base. We present a new model of knowledge representation called Bayesian Knowledge Bases. It unifies an if then style rules with probability theory. We can prove that such a merger remains fully probabilistic and yet maintains full flexibility and intuitiveness.
Descriptors : *KNOWLEDGE BASED SYSTEMS, *BAYES THEOREM, MATHEMATICAL MODELS, UNCERTAINTY, SEMANTICS, SYSTEMS ANALYSIS, OBJECT ORIENTED PROGRAMMING.
Subject Categories : Cybernetics
Distribution Statement : APPROVED FOR PUBLIC RELEASE