Accession Number:

ADA303824

Title:

Probabilistic Knowledge Base Validation

Descriptive Note:

Master's thesis

Corporate Author:

AIR FORCE INST OF TECH WRIGHT-PATTERSON AFB OH SCHOOL OF ENGINEERING

Personal Author(s):

Report Date:

1995-12-01

Pagination or Media Count:

91.0

Abstract:

Our work develops a new methodology and tool for the validation of probabilistic knowledge bases through- out their lifecycle. The methodology minimizes user interaction by automatically modifying incorrect knowledge only the occurrence of incomplete knowledge involves interaction. These gains are realized by combining and modifying techniques borrowed from rule-based and artificial neural network validation strategies. The presented methodology is demonstrated through BVAL, which is designed for a new knowledge representation the Bayesian Knowledge Base. This knowledge representation accommodates incomplete knowledge while remaining firmly grounded in probability theory.

Subject Categories:

  • Cybernetics

Distribution Statement:

APPROVED FOR PUBLIC RELEASE