Date of Award
Master of Science
Department of Electrical and Computer Engineering
Eugene Santos, Jr., PhD
This thesis develops a methodology and a tool for knowledge acquisition with the new probabilistic knowledge representation-the Bayesian Forest. It establishes the structure of the Knowledge Acquisition and Maintenance module of the Probabilities. Expert Systems, Knowledge and Inference (PESKI) architecture. The tool, MACK, is designed to be used directly by the domain expert(s) rather than by knowledge engineer(s), and thus supports automated knowledge acquisition. This research determines and implements the constraints necessary to ensure the consistency of Bayesian Forest knowledge bases as data is both acquired and subsequently maintained. The impact to the PESKI architecture of time-dependent information and default assumptions during reasoning is also explored. The tool has been applied to NASA's Post-Test Diagnostics System which locates anomalies aboard the Space Shuttles' Main Engines.
DTIC Accession Number
Banks, Darwyn O., "Acquiring Consistent Knowledge for Bayesian Forests" (1995). Theses and Dissertations. 6469.