STAR@LAVALVM1.BITNET (Spencer Star) (03/30/88)
This is a reply to KIKO's message asking about the validity of using
certainty factors in an expert system.
You can use certainty factors as a way of coping with uncertainty, but
you run the risk of introducing substantial errors in the analysis
due to the simplifying assumptions that underlie CFs. In some domains,
such as certain medical areas, the same treatment will be used to
cover several different diseases, e.g., antibiotics to cover infections of
various sorts. In that case, the incoherence introduced by using CFs is
often covered up by the lack of need to be very precise. I certainly
would not like to try to defend the use of CFs in a liability suit brought
against a person who made a poor diagnosis based on an expert system. I
would recommend doing a lot of research on the various ways that uncertainty
is handled by people working on uncertainty. An excellent starting point
is the paper, "Decision Theory in Expert Systems and Artificial Intelligence",
by Eric J. Horvitz, John S. Breese, and Max Henrion. It will be in the
Journal of Approximate Reasoning, Special Issue on Uncertain Reasoning,
July, 1988. Prepublication copies might be available from Horvitz ,
Knowledge Systems Laboratory, Department of Computer Science, Stanford
University, Stanford, CA 94305. This paper will become a standard
reference for people interested in using Bayesian decision theory
in AI.
Putting uncertainty into an expert system using decision theory is not
as simple as using certainty factors. But getting it right is not always
easy.
I hope this will be of some help. Best of luck.
Spencer Star (star@lavalvm1.bitnet) or
arpa: (star@b.gp.cs.cmu.edu)