[Pie a95]. N. Pie a. Cu en T ends in Quali a i e
Reasoning and Applica ions, Monog a la
CIMNE, 33. In e na ional Cen e o
Nume ical Me hods in Enginee ing,
Ba celona.
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o mes. Ph. D. Thesis Uni e si a Poli ecnica
de Ca alunya, Ba celona.
[Raiman86]. O. Raiman. O de o Magni ude
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Philadelphia, 100-104.
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Ams e dam.
[T a é-Massuyes&Pie a89]. L. T a é-Massuyes
and N. Pie a. Toe O de s o Magni ude
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74
Using cons ain p og amming amewo k o
Semiquali a i e Reasoning
R.M. Gasea, J.A. O ega, M. To o, J. To es and J.M. Co de o
Depa amen o de Lenguajes y Sis emas In o má icos.
Uni e sidad de Se illa
A da. Reina Me cedes s/n. Se illa (Spain)
{gasea ,jao ega, m o o,j o es,co de o }©lsi. us.es
Abs ac
A semiquali a i e model is he ep esen a ion o he wo ld by means o quali a i e and quan i a i e
knowledge. I is mo i a ed by he lack o quan i a i e knowledge in de e mined pa ame e s o a iables
o he model. We wish o ob ain conclusions and gene aliza ion de i ed om hese speci ic models ..
In his wo k, we show as semiquali a i e models may be ans o med o in e al cons ain sa is ac ion
p oblems(ICSP). The in e ence p ocess in an ICSP is based in combining cons ain p opaga ion and
b onch and bound algo i hms. The in e al domains o he a iables a e o p opaga e h ough he
cons ain s. A de ined ope a o mus exis o e e y quali a i e knowledge. l ans o ms his knowledge
o an in e al cons ain . The applica ion o he cons ain p og amming amewo k o a ICSP allows
he ob aining o conclusions in a au oma ic way.
Keywo ds: Quali a i e easoning, Cons ain P og amming, Consis ency echniques.
1 In oduc ion
Di e en communi ies ha e s udied he qua
li a i e ep esen a ion o he wo ld and hey
ha e p oposed o malisms o quali a i ely ea
son abou hese ep esen a ions. The main m
i a ions a e he lack o quan i a i e knowledge
and he excess o hem ha may ob ain conclu
sions and explana ions unde s andable by hu
mans. Gene ally he eal models a e no pu e
quali a i e o pu e quan i a i e bu a e no 
mally composed o quan i a i e and quali a
i e knowledge. l is known as semiquali a i e
model. Ali his knowledge mus be conside ed
when hese models a e s udied.
In he eigh ies, he main concep s o he quali
a i e echniques appea ed in he a ea o A i
icial In elligence(AJ), by means o he publica-
ion o he sys ems ENVISION [DeKlee 84],
QSJM[Kuipe s86] and QPT[Fo bus84]. Di 
en monog aphs ha e been published in he
90s [Weld90),[Fal ings92],[Kuipe s94],(Pie a95],
[Dague95],[T a e97], ha e lec he opics and
he cli e en de eloped echniques in quali a
i e easoning(QR). This quali a i e know
ledge is use ul o unde s and, in a simple way,
some o he p ope ies o he models, he 
o e he simplici y is i s p incipal p ope y. l
ha e been applied in di e en asks, such as su
pe ision and diagnosis o chemical indus ial
p ocess[Penal a91l[Bousson93](Chang93J, ma
ine mo o (Mo eno93), he con ol [Lepe i 87],
analysis o dynamical sys ems (A acil93]
[Gasca98], so wa e analysis [Xan hakis94] and
concep ual design o s uc u es in enginee ing
[Bozzo98]. In a majo i y o he app oaches o
modeling quali a i e easoning in Al, i is as
sumed explici ly o implici ly ha quali a i e
75
1