[mod.ai] Seminar - Induction, Knowledge, and Expert Systems

SAMY@gmr.com.UUCP (03/11/87)

Seminar at the General Motors Research Laboratories in Warren, Michigan.
Friday, March 20, 1987 at 10 a.m.



               INDUCTION,  KNOWLEDGE,  and   EXPERT  SYSTEMS


                             J. ROSS  QUINLAN
                   Head, School of Computing Sciences 
        New South Wales Institute of Technology, Sydney, Australia


                                ABSTRACT

This general talk examines inductive inference as a knowledge acquisition 
methodology, both from the perspective of the performance characteristics 
of the knowledge so acquired and its intelligibility.  A relatively simple 
class of induction methods that generate decision trees for classification 
tasks is outlined and illustrated.  A case study in which this approach was 
used to generate diagnostic knowledge in the domain of thyroid assays is
presented, and the performance of the decision trees is compared with that 
of a conventional expert system constructed by interviewing endocrinologists.
Finally, recent work in which decision trees are re-expressed as collections 
of production rules has been found to improve both the accuracy and 
comprehensibility of the inductively acquired knowledge.

Non-GMR personnel interested in attending please contact
R. Uthurusamy [ samy@gmr.com ] 313-986-1989