An Incompleteness Handling Methodology for Validation of Bayesian Knowledge Bases
Abstract
The PESKI (Probabilities, Expert Systems, Knowledge, and Inference) system attempts to address some of the problems in expert system design through the use of the Bayesian Knowledge Base (BKB) representation. Knowledge gathered from a domain expert is placed into this framework and inferencing is performed over it. However, by the nature of BKBs, not all knowledge is incorporated, i.e. the representation need not be a complete representation of all combinations and possibilities of the knowledge, as this would be impractical in many real-world systems. Therefore, inherent in such a system is the problem of incomplete knowledge, or spaces within the knowledge base where areas of lacking knowledge hinder arrival at a solution. Some of this knowledge is intentionally omitted but necessary for valid results. Intentional omission, a strength of the BKB representation, allows for capturing only the relevant portions of knowledge critical to modeling an expert's knowledge within a domain. This research proposes a method for handling the latter form of incompleteness administered through a graphical interface. The incompleteness is then able to be detected and corrected by the knowledge engineer in an intuitive fashion.
Document Details
- Document Type
- Technical Report
- Publication Date
- Dec 01, 1997
- Accession Number
- ADA337341
Entities
People
- David J. Bawcom
Organizations
- Air Force Institute of Technology