SIZZLE: A Knowledge-Acquisition Tool Specialized for the Sizing Task

Abstract

SIZZLE is a prototype knowledge-acquisition tool for building sizers: expert systems that solve sizing problems. SIZZLE uses an extrapolate­from-a-similar-case problem-solving method. Using this strategy, a sizer produces a solution by first becoming reminded of a source sizing case similar to a target sizing problem to be solved, and then adjusting the solution of the source case to account for the differences between the source and the target. The problem-solving strategy assumed by SIZZLE makes strong assumptions about the problem domain. SIZZLE assumes that knowledge about sizing can be organized as a collection of validated cases (each case is a problem-description/solution pair) and that similarities among problem descriptions imply similarities among solutions.