Reuse of constraint knowledge bases and problem solvers explored in engineering design

Reuse has long been a major goal of the Knowledge Engineering community. We present a case study of the reuse of constraint knowledge acquired for one problem solver, by two further problem solvers. For our analysis we chose a well known benchmark knowledge base system written in CLIPS, which was based on the propose-and-revise (P+R) problem solving method (PSM), and which had a lift/elevator knowledge base (KB). The KB contained 4 components, including constraints and data tables, expressed in an ontology which reflects the P+R task structure. Sufficient trial data was extracted manually to demonstrate the approach on two alternative problem solvers: a spreadsheet (Excel) and a constraint logic solver (ECLiPSe). The next phase was to implement ExtrAKTor, which automated the process for the whole KB. Each KB that is processed, results in a working system that is able to solve the corresponding configuration task (and not only for elevators). This is in contrast to earlier work which produced abstract formulations of the PSMs but which were unable to perform reuse of actual knowledge bases. Subsequently, we have used the ECLiPSe solver on some more demanding vertical transport (VT) configuration tasks. We found that we had to use a little-known propagation technique described by Le Provost and Wallace. Further, our techniques did not use any heuristic “fix”‟ information, yet successfully dealt with a “thrashing” problem that had been a key issue in the original VT work. Consequently, we believe we have developed a widely useable approach for solving this class of parametric design problem, by applying novel constraint-based problem solvers to data and formulae stored in existing KBs.