Knowledge reorganization. A rule model scheme for efficient reasoning

Abstract

Discusses the application of conceptual clustering in restructuring large knowledge bases for the purpose of improving their complex problem solving efficiency. The rule base of PLAYMAKER, a system for characterizing hydrocarbon fields and plays, is restructured into a hierarchy of rule models using our conceptual clustering scheme, ITERATE. The rule models, used with a task-specific reasoning methodology, provide a more efficient, focused, and robust inferencing mechanism. A set of case studies that have been conducted demonstrate the improved performance of the reasoning system. PLAYMAKER is implemented on MIDST (Mixed Inferencing Dempster-Shafer Tool), a general-purpose knowledge-based system construction tool that incorporates reasoning mechanisms based on a task-specific architecture and belief functions.<>