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1、HornClausesandFeature-StructureLogic:PrinciplesandUnicationAlgorithmsyStephenJ.HegnerUniversityofBergenDepartmentofInformaticsBergenHigh-TechnologyCenterN-5020Bergen,NorwayInternet:hegner@ii.uib.no(Revised:June1993)ThispaperappearsasReportNo.1,June1993,intheseriesReportsinLogic,Language,an
2、dInformation,publishedby:UniversityofOslo,DepartmentofLin-guistics,P.O.Box1102,N-0317Oslo,Norway.AnabbreviatedversionofthisreportappearsinthebookConstraints,LanguageandComputation,editedbyM.Rosner,C.J.Rupp,andR.Johnson,publishedbyAcademicPress,1994,pp.111-147.AbstractThedesirabilityofHorncl
3、ausesinlogicaldeductivesystemshaslongbeenrecog-nized.Thereasonsareatleastthreefold.Firstly,whileinferencealgorithmsforfulllogicsofanyreasonableextentaretypicallyintractable,forsystemsrestrictedtoHornclausesthepictureismuchbetter.(Forexample,inordinarypropositionallogic,whilethefullsatisabi
4、lityproblemisNP-complete,alinear-timealgorithmexistsforHornclauses.)Secondly,theknowledge-representationcapabilitiesofHornclauses,whileweakerthanthoseofthefulllogic,remainremarkablyrich;indeed,farricherthanthatofsimpleconjunctivelogicalone.Thirdly,Hornclausesdenethemaximalsubsetofafulllogi
5、cwhichhasthepropertyofadmittinggenericmodels,whichroughlymeansthatforanysetofHornclauses,thereisaleastmodeloftheclausesinthatset.ItisthepurposeofthispapertoinitiateaninvestigationofHornclauselogicforanextendedclassoffeaturestructures.Afterlayingthegroundworkforthiscontext,weprovidetwokeyres
6、ults.Intherst,weshowhowthepropertyofad-mittinggenericmodelscanbeextendedtofeaturestructurelogic,anddemonstratetheimportanceofthispropertyingeneralizingtheuseofordinaryfeaturestructuresinunication-basedformalisms.Oursecondcontributionisatractableunicationalgorithmforextendedfeaturestructu
7、resconstrainedbyHornclauses.Thisalgo-rithmisanintegrationofthetraditionalunicationalgorithmforfeaturestructuresandthelinear-timeinferencealgorithmforpropositionallogic.yCurrentaddress:DepartmentofComputerScienceandElectricalEngineering,VoteyBuilding,Uni