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):

Report Date:

1996-08-12

Pagination or Media Count:

22.0

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.

Subject Categories:

  • Cybernetics

Distribution Statement:

APPROVED FOR PUBLIC RELEASE