urquhart@utcs.UUCP (Prof. A. Urquhart) (07/25/85)
I am new to Expert Systems and I was wondering if an inductive learning machine had ever been used to generate correlations between properties defined to the system so as to come up with new rules (valid to some probability). Any literature on this? Andre Vellino !utcs!urquhart
tgd@orstcs.UUCP (tgd) (08/03/85)
Yes there are a number of applications of inductive inference techniques to the development of expert systems. The first, and perhaps best, was Meta-DENDRAL, which developed rules for the DENDRAL expert system. Also, the AQ11 system has been employed to develop rules for a plant pathology expert system. A few companies are marketing inductive inference programs for this purpose. Radian corporation is marketing something called RULEMASTER, which forms rules from examples. Human Edge is marketing Expert Ease, while builds decision trees from examples. Both of these systems, I believe, employ a method developed by Ross Quinlan called ID3. References: Meta-Dendral: See the AI Handbook, Volume 3. Also, Buchanan & Mitchell, in Waterman and hayes-Roth, Pattern-Directed Inference Systems, Academic Press. AQ11: Michalski, R. S., and Chilausky, R. L., Learning by being told and learning from exapmles: an experimental comparison of two methods of knowledge acquisition in the context of developing an expert system for soybean disease diagnosis. International Journal of Policy Analysis and Information Systems, Vol. 4:125-161, 1980. ID3: Quinlan, J. R., Learning efficient classification procedures and their application to chess endgames, in michalski, Carbonnell, and Mitchell, Machine Learning, Palo Alto, Tioga Press, 1983. See the latest Ai magazine for adds from Radian and Human Edge. --Tom Dietterich Oregon State University orstcs!tgd tgd%oregon-state@csnet-relay
holte@brueer.UUCP (Robert Holte) (08/12/85)
The only system I know of which generates rules for a knowledge base
on strictly probabilistic grounds is the RX system (R.L. Blum,IJCAI,1983).
The use of AI machine learning techniques to generate a knowledge base from
examples is strongly advocated by Donald Michie, who has made commercially
available knowledge engineering tools (e.g. EXPERT EASE, and RULEMAKER) for
this purpose. There has not been much published on the use of these tools,
and I would very much like to hear from anyone who has experience using them.
Michalski reported a striking case in which the knowledge base induced
from examples significantly outperformed those which had been engineered
in close collaboration with a human expert (International Journal of
Man-Machine Studies, vol.12, pp.63-87, 1980, and elsewhere), but he does not
appear to have carried out any similar studies since. A rule-learning module
was included in his ADVISE system for knowledge engineering, but I
have not heard anything about ADVISE since it was announced at IJCAI in 1983.
The successful domain was soybean disease diagnosis, and I believe a recently
begun ESPRIT project is attempting to extend this work to a wide class
of European plants and plant diseases.
I attended the International Machine Learning Workshop in June.
The topic of generating knowledge-bases from examples was discussed only
once, by Bruce Buchanan in his overview of learning research at Stanford.
Of the sixty-plus research summaries included in the workshop proceedings,
only a handful were concerned with this topic, namely those coming under
the general heading of Learning Apprentices. Learning Apprentices learn new
control (meta ?) knowledge or correct existing knowledge by observing a human
expert solving problems with the aid of a reasoning assistant (e.g. an ordinary
knowledge-based system): they are not intended to create new knowledge bases.
Most of the existing LAs will be described at IJCAI in Los Angeles (1985).
On the other hand, I have seen a proposal (not yet approved) for a joint
European project which specifically includes the general topic of automatic
knowledge acquisition for expert systems, and I have heard a rumor that there
will be a (relatively small) commercially-backed project on this topic in
Britain starting this year.
-- Rob Holte holte%brueer@ucl-cs
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