Debugging knowledge-based applications with a generic toolkit.

Knowledge refinement tools assist in the debugging and maintenance of knowledge based systems (KBSs) by attempting to identify and correct faults in the knowledge that account for incorrect problem-solving. Most refinement systems target a single shell and are able to refine only KBSs implemented in this shell. Our KRUSTWorks toolkit is unusual in that it provides refinement facilities that can be applied to a number of different shells, and is designed to be extensible to new shells. The paper outlines the components of the KRUSTWorks toolkit and how it is applied to faulty KBSs. It describes its application to two real aerospace KBSs implemented in CLIPS and POWER-MODEL to demonstrate its flexibility of application

Knowledge Modelling for a Generic Refinement Framework

Refinement tools assist with debugging a KBS's knowledge, thus easing the well-known knowledge acquisition bottleneck, and the more recently recognised maintenance overhead. Existing refinement tools are developed for specific rule-based KBS environments, and have usually been applied to artificial or academic applications. Hence there is a need for tools which are applicable to industrial applications. However, it would be wasteful to develop separate refinement tools for individual shells; instead, the KrustWorks project is developing re-usable components applicable to a variety of KBS environments. This paper develops a knowledge representation that embodies a KBS's rulebase and its reasoning, and permits the implementation of core refinement procedures, which are generally applicable and can ignore KBSspecific details. Such a representation is an essential stage in the construction of a generic automated knowledge refinement framework, such as KrustWorks. Experience from applying t..