Knowledge Systems Laboratory
Stanford University

Abstract: "Reducing" CLASSIC to practice: Knowledge representation theory meets reality

Most recent key developments in research on knowledge representation (KR) have been of the more theoretical sort, involving worst-case complexity results, solutions to technical challenge problems, etc. While some of this work has influenced practice in Artificial Intelligence, it is rarely if evermade clear what is compromised when the transition is made from relatively abstract theory to the real world. CLASSIC is a description logic with an ancestry of extensive theoretical work (tracing back over twenty years to KL-ONE), and several novel contributions to KR theory. Basic research on CLASSIC paved the way for an implementation that has been used significantly in practice, including by users not versed in KR theory. In moving from a pure logic to a practical tool, many compromises and changes of perspective were necessary. We report on this transition and articulate some of the profound influences practice can have on relatively idealistic theoretical work. We have found that CLASSIC has been quite useful in practice, yet still strongly retains most of its original spirit, but much of our thinking and many details had to change along the way.

Ronald J. Brachman, Deborah L. McGuinness, Peter Patel-Schneider, and Alex Borgida. ``"Reducing" CLASSIC to practice: Knowledge representation theory meets reality,'' In Artificial Intelligence 114 (1-2) pages 203-237, October 1999.

Return to Selected Papers of Deborah L. McGuinness.