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Knowledge Systems Laboratory
Stanford University
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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.
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