Date of Award
12-1995
Document Type
Thesis
Degree Name
Master of Science
Department
Department of Electrical and Computer Engineering
First Advisor
Eugene Santos, PhD
Abstract
Our work develops a new methodology and tool for the validation of probabilistic knowledge bases throughout 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.
AFIT Designator
AFIT-GCS-ENG-95D-04
DTIC Accession Number
ADA303824
Recommended Citation
Gleason, Howard T., "Probabilistic Knowledge Base Validation" (1995). Theses and Dissertations. 6143.
https://scholar.afit.edu/etd/6143