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