Uncertainty analysis of rule-based expert systems with Dempster-Shafer mass assignments
✍ Scribed by Michael A. S. Guth
- Publisher
- John Wiley and Sons
- Year
- 1988
- Tongue
- English
- Weight
- 910 KB
- Volume
- 3
- Category
- Article
- ISSN
- 0884-8173
No coin nor oath required. For personal study only.
✦ Synopsis
This article extends Dempster-Shafer Theory (DST) mass probability assignments to Boolean algebra and considers how such probabilities can propagate through a system of Boolean equations, which form the basis for both rule-based expert systems and fault trees. The advantage of DST mas3 assignments over classical probability methods is the ability to accommodate when necebsary uncommitted probability belief. This paper also examines rules in the context of a probabilistic logic, where a given rule itself may be true with some probability in the interval [O,l]. When expert system knowledge bases contain rules which may not always hold, or rules that occasionally must be operated upon with imprecise information, the DST mass assignment formalism is shown to be a suitable methodology for calculating probability assignments throughout the system.
I. INTRODUCTION
This article develops a methodology for rational inference of fault trees and rule-based expert systems with probabilistic interpretations on initiating events and rules themselves. The article also focuses on knowledge representation with imprecise information and how this form of uncertainty can be formulated into a system of Boolean equations. The analysis employs the method of assigning probability in Dempster-Shafer Theory (DST) and contains standard Boolean algebra operators defined over a three-valued logic domain of interest.