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Towards an Extensible Knowledge Refinement Tool

This paper describes the development of an extensible tool for automated knowledge base refinement. This tool, KRUST, is able to repair faults in rule bases implemented using a number of KBS development environments. This is in contrast to most knowledge refinement systems, which are restricted to a single formalism (usually predicate logic). KRUST achieves its generality through a few key features, specifically: a hierarchical, extensible representation for rule elements; a mechanism for querying an external KBS tool; a configurable KB parser; and a modular design that allows the addition of new features as appropriate. We argue that such a tool kit approach is needed if usable refinement tools are to be applied successfully to the tasks of knowledge acquisition and maintenance for knowledge-based systems.