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1、1ABehavioralModelforLinguisticUncertaintyPETERWALLEYandGERTDECOOMANyUniversiteitGent,OnderzoeksgroepSYSTeMSTechnologiepark9,9052Zwijnaarde,Belgium1.1INTRODUCTIONInformationiscommonlytransmittedthroughstatementsinnaturallanguage.Thestatement‘Maryisyoung’,forinstance,provides
2、partialinformationaboutMary’sage.IfinitiallyweknownothingaboutMary’sageandwesubsequentlyhearthatsheisyoung,ourknowledgeaboutheragehasincreased,althoughweremainuncertainaboutherexactage.Inthispaperweareconcernedwiththeinformationconveyedbystatementsinnaturallanguage,whichwec
3、alllinguisticinformation.Linguisticinformationofteninvolvesvaguepredicatessuchas‘young’.Wewillrestrictourdiscussiontosimpleaffirmativestatementsofthetype‘subjectispredicate’or‘subjectsatisfiesproperty’.Thelinguisticinformation‘Maryisyoung’producessomeuncertaintyaboutMary’sage
4、;itseemslikelythatMaryisyoungerthan30years,butwecannotbecertainaboutthat.Wewillcallthistypeofuncertaintylinguisticuncertainty.Ingeneral,linguisticuncertaintyistheuncertaintyaboutapreciselydefinedquantitythatisproducedbylinguisticinformation.Theproblemconsideredinthispaperish
5、owbesttomodellinguisticuncertainty.Inthisproblem,ouruncertaintyisduetoalackofknowledge,andnottosomephysicalrandomnessorindeterminacy.Ourmodelforlinguisticuncertaintywillthereforebeepistemicratherthanphysical(see[42]foradiscussionofthisdistinction).Whyisthisimportant?Foronet
6、hing,linguisticuncertaintyisverycommonanditisnaturalfromascientificoraphilosophicalpointofviewtoattempttomodelit.Anotherreasonismorepractical.Humanactionsareveryoftenbasedonlinguisticinformation.Inordertodesignsystemsthatemulate,mechanizeorimprovewhathumansdo,itisthereforeus
7、efultobeabletomodelthiskindofinformation.ForyResearchAssociateoftheFundforScientificResearchFlanders(Belgium)(F.W.O.).iiiABEHAVIORALMODELFORLINGUISTICUNCERTAINTYinstance,manyoftheproductionrulesinexpertsystemsareexpressedinnaturallanguageandcontainvaguepredicates;see[16,55]f
8、ormanyexamples.Tocombinesuchrulesandtodrawinferencesormakedecisionsfromthem,itisne
