Path: utzoo!attcan!uunet!mcsun!ub4b!prlbcom!lln-cs!bdn
From: bdn@lln-cs.UUCP (Denis Ballant)
Newsgroups: comp.ai
Subject: Definition of Expert Systems
Message-ID: <980@lln-cs.UUCP>
Date: 21 Mar 90 16:28:58 GMT
Reply-To: bdn@info.ucl.ac.be (Denis Ballant)
Organization: UCL - Unite d'Informatique, LLN, Belgium
Lines: 111

What is an expert system (ES) ?
To arouse  some   discussion about this  topic,  I submit you
several common definitions (found in the literature).

I hope that this discussion will be valuable to have a better
comprehension of this often misunderstood term.

Denis Ballant.
bdn@info.ucl.ac.be

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1. 1st Definition [Clan 89]

Expert  systems  handle  heuristics  and uncertain knowledge;
their reasoning is qualitative and  imprecise. In contrast to
quantitative models (involving mathematical laws  as found in
physics), expert systems contain qualitative world models.


2. 2nd Definition [Mich 86]

An expert system    is   a  computer system     that achieves
performance comparable to a human expert at  solving problems
in   some  task  domain   by utilizing   a   large  amount of
domain-specific  knowledge.   Because  of    the  substantial
amounts of knowledge required, the knowledge acquisition task
assumes major proportions.


3. 3rd Definition [Ole 86]

Les   syst`emes  experts   se comportent  comme  des  experts
humains. Ceux-ci ont r'euni, dans le domaine pour  lequel ils
sont experts, des  connaissances  pr'ecises et s^ures. Gr^ace
`a celles-ci ils peuvent  porter des diagnostics et r'epondre
aux questions  qui portent  sur ce  domaine.    Les syst`emes
experts fonctionnent  de cette mani`ere. Ils  comportent deux
'el'ements principaux:  une  base de   donn'ees et un  moteur
d'inf'erence.      Ils    correspondent  respectivement   aux
connaissances  acquises, stock'ees   dans    la  m'emoire  de
l'ordinateur,  et au raisonnement qui permet,   `a partir des
informations communiqu'ees,  de  porter le diagnostic.    Les
syst`emes experts assurent une gestion des connaissances.  La
constitution  de  la  base de  donn'ees   se r'ealise  par la
consultation, l'interview d'experts humains  qui communiquent
le   savoir  que  l'ordinateur  va    enregistrer  et ensuite
exploiter.


4. Misc: [Sowa 84]

Expert systems  can  be  grouped  in  three major  categories
according to the kinds of problem they address:
 a. Classification systems. Ex: MYCIN
 b. Design systems. Ex: R1
 c. Decision support systems (DSS).


5. Misc: [Greg 88]

Three Expert System problem-solving philosophies:
 a. shallow knowledge approach
 b. model-based reasoning approach (Steels 1985)
	Constraint:  representation of behavioral models
	of  complex entities   must be   allowed by  the
	knowledge representation formalism.
 c. structured reasoning approach
	Make  the structure  of  the  reasoning  process
	explicit, and organize the reasoning  process by
	means   of   a comparison   of  elementary tasks
	operating   on  specific   blocks of  knowledge.
	Constraint: The  partitioning of  the   KB  into
	role-specific components with   selective access
	must be allowed.


6. References:
--------------

[Sowa 84]
	Sowa John F.,
	Conceptual Structures -- Information Processing in Mind and Machine,
	Addison-Wesley, 1984.

[Greg 88]
	Gr'egoire Eric,
	Evaluation of the expert system tools KEE and ART: 
	a case study,
	Applied Artificial Intelligence, Vol. 2, Num 1,
	R.Trappl (ed.), Hemisphere, New-York, 1988, pp.1--23.

[Clan 89]
	Clancey William J.,
	Viewing knowledge bases as qualitative models,
	IEEE Expert, Summer 1989.

[Mich 86]
	Michalski Ryszard S., Carbonell Jaime G., Mitchell Tom M.,
	Machine Learning: An Artificial Intelligence Approach,
	Vol.2, Morgan Kaufmann Publishers, Palo Alto, CA, 1986.

[Ole 86]
	Ol'eron Pierre,
	L'intelligence, Presses Universitaires de France,
	Collection ``Que sais-je ?'', Num 210, 4th edition, 1986.