🚀 go-pugleaf

               University of New South Wales

         School of Computer Science and Engineering

             Artificial Intelligence Laboratory

                       Seminar Series
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TITLE:     Induction of Ripple-Down Rules

WHO:       Paul Compton AI Lab, UNSW

WHEN:      1-2pm, Friday, November 27, 1992.

ABSTRACT:

Knowledge-based systems with large  structures  of  concepts
and  rules  are  now in routine in a number of applications.
Knowledge acquisition of these systems as new  circumstances
arise is an ongoing requirement that increases in difficulty
as the system grows due to interaction  between  rules.  The
use of rule structures with two forms of exceptions (if-true
and if-false links) establishes a well-defined  context  for
each  decision  such  that corrections may be made by adding
only one rule that is guaranteed to  effect  only  a  small,
well-defined set of previous cases.  The successful applica-
tion of such "ripple-down" rule structures to  building  and
maintaining  knowledge  bases  has been previously reported.
The limitation of this method is that the knowledge base may
end  up  with the same knowledge repeated throughout causing
the expert to do unnecessary work. This paper reports on the
development  of  an algorithm for the automatic induction of
ripple-down rules and produces  substantially  more  compact
knowledge  structures  that the manual method, but which can
then be maintained further using the manual method.

This work is a report  of collaboration between  Brian Gaines
(University of Calgary) and myself and was recently presented 
at AI '92 in Hobart.

WHERE:     Rm 212, Samuel Building, University of New  South
           Wales.  Enter off Botany Street, stop at gate and
           ask grey men for day pass and instructions.  Park
           in  the  main car park on your left.  The Samuels
           building is the gray building directly behind the
           gates  with  strange shield-like objects over the
           windows.

INQUIRIES: timm@cs.unsw.oz.au (Tim Menzies)

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