AIAI-TR-193 AIAI. October1993

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1 DevelopmentofaKBSforPersonalFinancial PlanningGuidedbyPragmaticKADS SusanneDirks IBMIreland Dublin Dept.ofArticialIntelligence UniversityofEdinburgh MandyHaggith UniversityofEdinburgh JohnK.C.Kingston1 AIAI-TR-193 AIAI October1993 Thisarticlewaspublishedinthejournal\ExpertSystemswithApplications", 9,2,1995,pp ArticialIntelligenceApplicationsInstitute ctheuniversityofedinburgh,1996. UniversityofEdinburgh EdinburghEH11HN UnitedKingdom 80SouthBridge 1Authortowhomallcorrespondenceshouldbeaddressed

2 PragmaticKADS[6].2Theaimoftheprojectwasthedevelopmentofa titleddevelopmentofakbsforpersonalfinancialplanningguidedby totypesystemdevelopedassistsapotentialprivateinvestorinselectinga professionallybalancedmixtureofinvestmentproductsthatmeetsallthe prototypeknowledge-basedsystemforpersonalnancialplanning.thepro- Thispaperoutlinesthestructureandtheresultsofaresearchproject Abstract investor'srequirementswithregardtotheinvestment.aspartofthespecication,itwasdecidedthattheprototypeistodevelopaportfolioforasingle methodology,astreamlinedversionofkadssuitabletothedevelopmentof type.thedevelopmentprocessshowedthatthemodelsthataredeveloped smallandmedium-sizedsystems.thepaperthereforedescribeshowprag- clientinvestingaone-olumpsum,assumingthattheclient'spension,insuranceandmortagehavebeenarrangedandthatnootherpriorinvestmentmatickadshelpedtoguideandstructurethedevelopmentoftheproto- needtobetakenintoaccount. viewpoints,contributebothtobreakingdownthecomplexityoftheproblem aspartofkadsknowledgeanalysis,whichviewknowledgefromdierent andtoensuringacomprehensiveknowledgeanalysis.italsoshowedthatthe ThedevelopmentoftheprototypewasguidedbythePragmaticKADS solvingstrategies.thispaperpresentsawayinwhichthisproblemcanbe thelow-levelknowledgethatmayhaveanimpactonthehigh-levelproblem- top-downapproachofkadshastheinherentdangerofneglectingsomeof FinancialPlanningGuidedbyPragmaticKADS.Asthenamesuggests,thepurpose ThispaperdescribesaresearchprojectentitledDevelopmentofaKBSforPersonal 1Introduction development[9],guidedbykads. resolvedbyusingamodiedversionofthespiralapproachtoexpertsystem Thisindicatesthatimplementingaknowledgebasedsystemtoperformpersonal oftheprojectwastodevelopaknowledgebasedsystemwhichassistedinthetaskof nancialplanningisbothfeasibleandpossiblybenecial;indeed,severalknowledge personalnancialplanningthereforefullsthecriteriaforbeingan\experttask". preparinganancialplanforanpotentialprivateinvestor.thisrequiresselection basedsystemshavepreviouslybeencommerciallydevelopedtoperform,orassist ofamixtureofnancialproductswhichisbothprofessionallybalancedandmeets inperformingpersonalnancialplanning.companieswhohavedevelopedsuch carriedoutbyatrainedsalesforce,andisunderstoodbyveryfewuntrainedpeople; alltheclient'srequirementswithregardtotheinvestment.thistaskisnormally DepartmentofArticialIntelligence,UniversityofEdinburgh. 2Theworkwascarriedoutwhiletherst-namedauthorwasapostgraduatestudentofthe 1

3 Bank[12]intheUSA,andSanwaBank[7]andDai-IchiKangyoBank[17]inJapan. ology[13].pragmatickadsisastreamlinedversionofthekadsmethodology. KADS(KnowledgeAcquisitionandDocumentStructuring)[20]isastructured bankingermany[22],appliedexpertsystemsinc.[2]andchaselincolnfirst Forreviewsofapplicationsinthiseld,see[11]or[10]. systemsincludeallieddunbar[1]andsterlingwentworth[10]intheuk,thebhf approachtothedevelopmentofknowledgebasedsystemsandassuchistobe seenincontrasttounstructuredapproachessuchasrapidprototyping.therehave beenpreviousattemptstoperformstructuredanalysisoftheknowledgerequired toperformpersonalnancialplanning(e.g.thecompassyssystemwasdeveloped\accordingtoslightlymodiedrulesofinformationengineering"[22]),but ThedevelopmentofthesystemwassupportedbythePragmaticKADSmethod- acquiredknowledgecouldbeproposedasarststeptoproducingusefulmodelsof specicmethodstoconstructanexpertsystemforpersonalnancialplanning.this projectwasthereforeabletoachieveamethodologicalpurposeaswellasproducinganimplementedsystem:thestrengthsandweaknessesofthepragmatickads fewrecordsareavailableofsuchattempts,andtherearenoknownusesofkbs- approachestonancialplanning,andofnancialproducts. methodologyonareal-lifeprojectcouldbeevaluated,andthemodellingofthe durationoftheproject,thefollowingsimplifyingassumptionsweremade: theinvestorissingle; theinvestordoesnothaveanexistingportfoliothatneedstobetakeninto Inordertoreducethecomplexityoftheproblemtoatractablesizeforthe theinvestorwantstoinvestasinglelumpsum,asopposedtoaseriesof account; relevanttotheinvestor,butdonotmateriallyaecttheprocessofpreparinga personalnancialplan. Theseassumptionsrestrictthenumberofnancialproductswhichmightbe theinvestor'sinsurance,mortgageandpensionarrangementshavebeensorted out,andsodonotneedtobeconsidered. regularpayments; tion2,theunderlyingideasandprinciplesofboththekadsandthepragmatic KADSmethodologyareoutlined.Insection3,themostimportantresultsofthe knowledgeacquisitionandelicitationstagearedescribed.insection4,theknowledgeandunderstandingofthetaskobtainedintheprevioussectionsisanalysed withintheframeworkofaspiralapproachtoexpertsystemdevelopment.insec- knowledge-basedsystemwasdevelopedundertheguidanceofpragmatickads Thefollowingsectionsprovideaconciseaccountofhowtheprototypeofa 2

4 withtheaidofkadsmodels.insection5,themostimportantpartofthedesign stageofsystemsguidedbypragmatickads,thestageofbehaviouraldesign,is discussedinsomedetail.section6explainswhyaniterationofknowledgeacquisition,analysisanddesignbecamenecessarywhenimplementationofthesystemwas started.finally,insection7,theinitialaspirationsarecontrastedwiththenal assessed. 2KADSandPragmaticKADS AccordingtoKADS,developmentofaknowledgebasedsystemistobeseenasa forthedevelopmentofaknowledge-basedsystemforpersonalnancialplanningis achievementsoftheprojectandtheusefulnessofthepragmatickadsmethodology ofabstractionaredeveloped.thisisintendedtoprovideastructuredmethodfor modellingprocess,duringwhichmodelsoftheacquiredknowledgeatdierentlevels theinferencelayer:adeclarativedescriptionoftheproblem-solvingtask; transformingtheexpertiseextractedfromtheexpertintothecodeoftheplanned knowledge-basedsystem.duringtheknowledgeanalysisstage,themostimportant KADSmodelisthefour-layermodelofexpertise,whichdividesproblem-solving thestrategylayer:theintegrationofdierentproblem-solvingtasks. thetasklayer:aproceduraldescriptionoftheproblem-solvingtask; intofour\layers": thedomainlayer:thestaticconceptsandrelationsspecictothedomain; stagesofexpertsystemdevelopment.theoverallkadsmethodologyprovides designstages;forexample,thestageofbehaviouraldesignisguidedby\probing questions"derivedfromtheapproachofklineanddolins[16]whichhelptoselect considerablylessdirectguidanceduringdesignandimplementation,exceptfor recommendingthatthesestagesshouldstrivetomaintainthestructuredeveloped duringthepreviousstages.pragmatickadsprovidesmoresupportforthevarious KADS'inuenceismostpervasiveduringtheknowledgeacquisitionandanalysis themostappropriateaiimplementationtechniques. 3KnowledgeAcquisition Thersttwostagesinthedevelopmentofaknowledge-basedsystem,wellbefore analysis.knowledgeacquisitionconsistsofthecollectionoftheknowledgethat designandimplementationcanevenbethoughtof,areknowledgeacquisitionand governsthedecision-makinginthedomain;knowledgeanalysisconsistsoftheinterpretationofthatknowledge. 3

5 decisionsconcerningtheoverallstructureoftheclientportfolioandverylow-level decisionsgoverningtheselectionofparticularinvestmentproductsascomponents ofaclientportfolio.theknowledgeusedinthekbsisbasedontwosources: publishedliteratureonpersonalnancialplanning; Knowledgeacquisitionforthisprojectfocusedbothonveryhigh-levelstrategic areaofpersonalnancialplanning,i.e.oftheinvestmentproductsavailableonthe aseriesofthreeknowledgeelicitationinterviewswithaprofessionalnancial thenecessaryinformationabouthowaportfolioforaclientwassystematically products,itwasrstandforemosttheinterviewswiththeexpertthatprovided marketandoflow-levelrulesofthumbfordecidingbetweendierentinvestment Whilethewrittenliteraturewasusefulingainingabasicunderstandingofthe advisor. constructed. tationstrategies,suchasthe20-questionstechnique[4],protocolelicitation[18], andthecardsort[8]wereemployed.the20-questionstechniqueandtheprotocol analysisofacasestudygavesomeimportantcluesabouttheproceduralapproach adoptedbytheexpert;inparticular,theyshowedthattheexpertconsidereda portfoliotoconsistofthreemaincomponents,whicharedesignedinthefollowing sequence: Duringthethreeinterviewswiththenancialexpert,severalknowledgeelici- theemergencyfund:easilyaccessibleinvestmentsforsuddenandunexpected theincomefund:investmentsdesignedtoprovidearegularincome; thegrowthfund:investmentswithvaryingdegreesofriskdesignedtoprovide nancialcrises; theportfolio.theresultofthecardsorthelpedtobuildaninitialbridgebetween investmentproducts{eachofwhichwasprintedonasinglecard{accordingto ofinvestmentproducts.thecardsortinvolvedtheexpertsortingallimportant theirmembershiptooneormoreofthethreeabove-mentionedmaincomponentsof Thecardsort,incontrast,focusedonthelow-levelknowledgeintheform capitalgrowth. ingisbelievedtobeuniqueamongstkbswhichperformorassistwithpersonal nancialplanning.thefewpreviouspublicationswhichmentionknowledgeacquisitionindicatethatknowledgeacquisitionhasbeenperformedbyinterviewing(e.g. strategiesemployedbytheexpert. thelow-levelknowledgeextractedfromtheliteratureandthehigh-levelreasoning [5])and/orprototyping(e.g.[7]). Theapplicationofstructuredknowledgeelicitationtechniquessuchascardsort- 4

6 4KnowledgeAnalysis Whilstthefocusofknowledgeacquisitionisoncollectingandcompilingknowledge fromdierentsourcesbymeansoftraditionalknowledgeacquisitionmethods,duringknowledgeanalysisthefocusshiftsawayfromtraditionalknowledgeacquisition methodstokadsmethodsasthemaintoolsforanalysingtheknowledgeacquired. 4.1TheDomainLayer developmentofthethreelayerswhichwereusedinthisprojectaredescribedbelow. Thedomainlayerconsistsofthestaticconceptsandrelationsspecictothedomain AspartofKADS-guidedknowledgeanalysisafour-layermodelofexpertiseisdeveloped,includingthedomain,theinference,thetaskandthestrategylayer.The ofexpertisebeingmodelled.inthedomainofpersonalnancialplanning,themost importantconceptsare: themaincomponentsofaportfolio(theemergencyfund,theincomefund, theinvestmentproductstypes,e.g.thetessaaccount; theinvestmentproductcategories,e.g.thebuilding-societyaccount; thespecicinvestmentproducts,e.g.thestroudandswindontessaaccount. andthegrowthfund); 5

7 Investment Portfolio is-part-of is-part-of is-part-of Emergency Fund Income Fund Growth Fund is-a is-a is-a is-part-of is-part-of bank account building society account life insurance safe growth fund pure growth fund instant access acount National Savings is-part-of is-part-of is-part-of notice account National Savings income bond low risk pure growth fund medium risk pure growth fund high risk pure growth fund National Savings investment account unit trusts high interest cheque account back-to-back arrangements investment trusts investment bonds gilts societyaccountistypicallyusedforanemergencyfund.theemergencyfundis relations.forexample,thestroudandswindontessaaccountisaninstance ofatessaaccount.atessaaccountisabuilding-societyaccount.abuilding- Figure1:Top-levelDomainModelforPersonalFinancialPlanning with-profit bonds shares annuities capital bond series D business expansion FIRST option bond schemes terviewswiththeexpertcanbeintegratedintoasetof\domainmodels",asrec- partoftheclientportfolio. Therelationsbetweentheseproductsareeitherpartof,isa,orinstance Thedomainknowledgeextractedfromboththewrittenliteratureandthein- discretionary off-shore funds 5th issue 37th issue savings managment funds index-linked certificate certificate 6

8 usefulforthreemainreasons: modelledinagraphicalmannerusinghardy,ahypertext-baseddiagramming package[21]. beseeninfigure1.thisgraphicalapproachtodomainmodellingwasparticularly ommendedbycommonkads3.thedomainofpersonalnancialplanningwas 2.itwasideallysuitedforrepresentingthefactthatsomeinvestmentproducts 1.itmadeitpossibletobreakdownthecomplexityofthedomainandviewit Thetop-leveldomainmodelforthedomainofpersonalnancialplanningcan 3.itallowedforeasymodicationandexpansionofthedomainmodel. belongtomorethanoneinvestmentproductcategory; atdierentlevelsofdetail; 4.2TheInferenceLayer solvingtask4. layer.modellingoftheinferencelayerinvolvestwoimportantsteps:rst,an ThesecondlayerofexpertiseintheKADSknowledgeanalysisistheinference interpretationmodelisselectedfromthekadslibraryofpredenedinterpretation handbyinstantiatingitintoaninferencestructure.aninterpretationmodelisa models,thentheselectedinterpretationmodelisadaptedtotheexperttaskat diagrammaticdeclarativedescriptionoftheinferencesrequiredinatypicalproblem- Thesecategoriesareeachmadeupoffurthersub-categories.Forexample,system synthesiscomprisestransformation,design,planning,andmodelling.designin oneofthreecategories:systemmodication,systemanalysis,andsystemsynthesis. usedomain-independentproblem-solvingstrategies.interpretationmodelsfallinto anumberofmodels,eachsuitedtoadierenttypeoftask;theunderlyingideais that,whilethedomainofeachkbstendstobeveryspecic,expertsnonetheless TheKADSlibraryofpredenedinterpretationmodels(seegure2)contains conguration,andrenementdesign. turncanbefurthersubdividedintoexploration-baseddesign(n.b.thismodelis uniquetopragmatickads{see[15]),transformationdesign,hierarchicaldesign, theterm\interpretationmodel"isoftenusedtoreferonlytothisdiagram. inferencesteps;however,theothercomponentsofinterpretationmodelsareusedsorarelythat ment.see[24]fordetailsofdomainmodelling. 4Strictlyspeaking,thereismoretoaninterpretationmodelthanjustthediagramofgeneric 3CommonKADSisthesuccessortotheKADSmethodology.Itisiscurrentlyunderdevelop- 7

9 Repairing SYSTEM MODIFICATION Controlling Maintaining Remedying Prediction of behaviour Diagnosis SYSTEM ANALYSIS Prediction Prediction of values Classification Simple classification Identifying Monitoring Assessment Explorationbased design Transformation Transformational design theknowledgeengineercanworkherwaydowntothemostsuitableinterpretation Single stream model,stepbystep.inpragmatickads,theselectionofthemostadequate Theideaofthishierarchicallyorderedlibraryofinterpretationmodelsisthat Figure2:LibraryofInterpretationmodels SYSTEM Refinement refinemt design Design SYNTHESIS design Multiple stream 8 Hierarchical refinemt design design Planning Configuration Modelling

10 interpretationmodelisalsoguidedbyabatteryofquestionswhichpointtothe bestchoiceofinterpretationmodel[13]. interpretationmodelforhierarchicaldesigntaskswaschosenasthemostsuitable modelforthetaskofpersonalnancialplanning.thismodelwaschosenforthe followingreasons: 1.Thetaskofpersonalnancialplanninginvolvescomposinganewstructural Basedontheknowledgeelicitedduringtheinterviewswiththeexpert,the 2.Thetaskofpersonalnancialplanninginvolvesdesigninganartefactwhich purposeoftheinvestment,butdoessowithoutapredenedframework.the meetscertainconstraints,suchastheclient'srequirementswithregardtothe developed.thetaskthereforefallsintothecategoryofsystemsynthesis; itiseectivelyimpossibletoenumerateallpossibledescriptionsthatcanbe descriptionofapossibleobject,aninvestmentportfolio,withinthedomain; 3.Thetaskofpersonalnancialplanningistackledbybreakinganancialplan intosubcomponents,suchastheemergencyfund,theincomeandthegrowth taskthereforebelongstothecategoryofdesign; fund,anddesigningeachofthesesubcomponentsindepedently.thereforethe taskcanbebestdescribedasoneofhierarchicaldesign. 9

11 Model Set select Functional Specification Skeletal Model decompose Functional Components Figure3:TheKADSInterpretationModelforHierarchicalDesign specify Functional Specification 10 design Design compose Composed match Design Model

12 set of 4 investment models select client-specific constraints skeletal investment model decompose sequence of functional components of chosen model Figure4:TheFinalInferenceStructureforPersonalFinancial specify procedural design specification each functional theyrepresent.theresultinginferencestructurecanbeseeninfigure4. 3.Thisinterpretationmodelwastheninstantiatedintoaninferencestructureby functions)intheinterpretationmodelwiththeentitiesoftheproblemdomainthat replacingtheboxes(knownasknowledgeroles),andtheovals(knownasinference TheinterpretationmodelforhierarchicaldesigntaskscanbeseeninFigure Planning component 11 provisional design design models final design model of design each functional compose match of investment investment component portfolio portfolio

13 availableskeletalinvestmentmodels(theincomemodel,themixedincome/growth Firstofall,theclient'sconstraints,inparticularhermaininvestmentobjectiveand thelevelofincomesherequiresfromtheinvestment,arematchedwiththefour model,thehighincomemixedmodel,andthegrowthmodel),andthemostsuitable skeletalinvestmentmodelisselected.thisskeletalmodelisthendecomposedinto asequenceoffunctionalcomponents.forexample,inthecaseofthegrowthmodel, TheinferencestructureinFigure4canbeinterpretedinthefollowingmanner: growthfund.thedesignprocedureforeachofthefunctionalcomponentsisthen componentshavebeendesigned,theyarecomposedtoformaprovisionalinvestmentportfolio,which,afterbeingmatchedwithfurtherclient-specicconstraints, specied,therebytakingintoaccountclient-specicconstraints.incontrasttothe thesequencestatesthatanemergencyfundshouldbeallocatedrst,followedbya inthenextstep,wheneachfunctionalcomponentisdesigned.afterallfunctional becomesthenaltailor-madeinvestmentportfolio. predenedinterpretationmodel,theclient-specicconstraintsarealsoconsidered 4.3TheTaskLayer ofthetask. Althoughtheinterpretationmodelshowstheinferencestepsperformedduringa particulartask,itdoesnotgiveanyindicationoftheexactproceduralordering thefollowingtaskmodelwasdeveloped: oftheinferences.suchproceduralorderingishighlighedbythetaskmodelwhich providesaproceduraldescriptionofthetaskandassuchoersadierentviewpoint Goalassistaprivateinvestorindesigningaportfoliotailoredtohisrequirements Taskdesign-investment-portfolio-for-client Onthebasisoftheinformationprovidedbytheexpertintheinitialinterview, Beginbyobtaininginitialinformationfromtheclient Selecttheskeletalinvestmentmodelthatbestmeetstheclient'srequirementsfromthesetofinvestmentmodels Decomposethechoseninvestmentmodelintoasequenceoffunctional components Specifyeachcomponent'sdesignprocedure sionoftheinvestmentportfolio,herebypayingattentiontotheskeletal Composeandlinkthefunctionalcomponentstoformaprovisionalver- Foreachfunctionalcomponent designprocedure,herebypayingattentiontoclient-specic Designeachfunctionalcomponentaccordingtothecomponent requirements 12

14 5Design Figure5:TaskStructurefordesigninganinvestmentportfolio model Matchtheprovisionalversionoftheinvestmentmodelwiththeclient's Thesoftwareengineeringlife-cycleofconventionalcomputersystemsisgenerally requirementstoobtainthenalversionofinvestmentportfolio ofexpertsystems,whereaprototypeisdevelopedveryquicklyandthenrepeatedly shouldnotonlyguideandstructuretheknowledgeacquisitionandanalysisstages, butshouldalsoprovidesomeadviceonhowthedesignandimplementationofthe modied,expanded,validated,andtested.ifkads'aimistointroduceamore methodologicalapproachtowardsthedevelopmentofexpertsystems,thenkads tion.suchdevelopmentistobeseenverymuchincontrasttotheusualdevelopment characterisedbythestrictlysequentialstagesofanalysis,design,andimplementa- systemshouldproceed. implementationshouldprogress,exceptforemphasizingthatbothstagesshould acquisitionandanalysisstages,itdoesnotgivemuchdirectiononhowdesignand strivetomaintainthestructureofthemodelofexpertisedevelopedduringthe previousstages. However,comparedtotheguidancethatKADSoersduringtheknowledge threestages: ventionalcomputersystemsandsubdividesthedesignprocessintothefollowing 1.functionaldesign; 2.behaviouraldesign; 3.physicaldesign. KADS-guideddesignthereforeproceedsinasimilarfashiontodesignforcon- furtherbelow. KBSandconventionalsoftware.Thereisalittleguidanceonbehaviouraldesignin gies,knowledgerepresentations,andinferencetechiques.thisguidanceisdescribed KADS;however,PragmaticKADSoersguidanceonappropriatecontrolstrate- representationandinferencetechniques,aprocesswhichdiersgreatlybetween ventionalsoftware,itisbehaviouraldesignthatdealswithselectionofknowledge WhilefunctionaldesignandphysicaldesigndonotdiersignicantlyfromconsignandAIimplementationtechniquesfortheimplementationstage.InPragmatic 5.1BehaviouralDesign Thepurposeofbehaviouraldesignistoselectthemostsuitableexpertsystemde- 13

15 KADS,thisstageissupportedby\probingquestions",whicharepartiallyderived answerstowhichhelpthesystemdesignerinselectingthemostsuitableknowledge fromtheworkofklineanddolins[16].thisisacollectionofspecicquestions,the representationandinferencetechniqueswithregardto: theoverallarchitectureofthesystem; theknowledgerepresentationstrategies; theinferencetypes; thecontroloftheowofinference; thehandlingofuncertaintyinknowledge; systemdevelopedtosupportpragmatickads[19].thelatterhelpstoselectthe mostsuitableaitechniquesandgivesascoreandexplanationforthemethod questionsisbasedbothonmaterialcoveredbyklineanddolinsaswellasthepdq theknowledgeacquisitionstrategy. Inthecaseofthesystemforpersonalnancialplanning,theresultoftheprobing theuserinterfaceandgeneralinput/outputmechanism; chosentoindicatehowstrongthesupportingevidencefortherelevantmethodis. wereselected: Theoverallarchitectureofthesystem:Shallowreasoning,asopposedtomodel Asaresultoftheprobingquestions,thefollowingAIimplementationtechniques Theknowledgerepresentationstrategies:Bothrulesandframeswerechosen basedreasoning,waschosenasthemostsuitablearchitecturalparadigmfor developmenttimeislessthansixmonths. threereasons.first,thetaskcanbedescribedbyaproceduralrepresentation anddoesnotrequireexplanationsintermsofcauseandeect;andlast,the asknowledgerepresentationtechniques.rulesareusedtorepresentthelarge andpoorlystructuredcollectionofindependentheuristicsthatcanbefound oftheexpert'sproblem-solvingsteps;second,theproblemspaceisshallow forarepresentationinformofrules.framesareusedtorepresentthewellstructured,hierarchicallyorderedsetofstaticknowledgeofdomainconcepts thatwasmodelledinthedomainlayer.theformatofthesehierarchically vestment,interestpaid,taxliability,andsimilarfactorsandisthussuitable inthedomainofpersonalnancialplanning.mostoftheseheuristicscanbe orderedfactscanbedescribedintermsofslotsforminimum/maximumin- forrepresentationbymeansofaninheritancetechnique,i.e.frames. describedintermsofif-thenstatementsandarethereforeparticularlysuitable 14

16 Theinferencetype:Data-drivenreasoning,asopposedtogoal-directedreasoning,waschosenasthedirectioninwhichinferenceshouldproceed.Datadrivenreasoningissuitablebecausealotoffacts,suchasclientdetails,are availableatthestart.thesefactsarethenusedtondasinglesolution wardchainingrules. rule-basedkbs,data-drivenreasoningistypicallyimplementedusingfor- amongstthegreatnumberofsolutionsthatmightbepossible.becauseof data-drivenreasoningwasselectedasthemostsuitableinferencetype.in boththeavailabilityofdataandthepossiblyverylargenumberofsolutions, Thecontrolofowofinference:Regardingthecontroloftheowofinference,itwasdecidedthatsearchshouldproceedinadepth-rstratherthana breadth-rstmanner.themainreasonforthisdecisionisthatthesearchtree Thehandlingofuncertainy:Ingeneral,thereislittleuncertaintyinthetask inthetree).duetothehighbranchingfactorandthelownumberoflevels inthetree,depth-rstsearchismoresuitablethanbreadth-rstsearch. onlyfourlevelsofdepth{thefundtype,theinvestmentproductcategory,the investmentproducttype,andtheinvestmentproduct(thelatternotshown forproductselection(seefig.1)hasahighbranchingfactorandconsistsof Theuserinterfaceandgeneralinput/outputmechanism:Regardingtheuser ofpersonalnancialplanning.theexceptiontotheruleisthedevelopment posetheportfoliobecauseitdoesnotachievetheincomeneeded.sincethis ofthehighincomemixedmodel,whereitmaybecomenecessarytodecom- thenancialadvisorgivestohisclienttocomplete.furthermore,oneshould questionsfromtheuser.inawaythiscorrespondstothequestionnairethat interface,amultiple-selectionmenuwasseenasanadequatewayofeliciting considering.however,thiswasnotincludedintheprototype. involvesfalsifyingassumptions,atruthmaintenancesystemmaybeworth Knowledgeacquisition:Ifthesystemwastoincludeautomaticknowledgeacquisition,whichtheprototypedoesnot,thebestwaytodothiswouldbe becausethedecisivefactorsinmostnancialproblemcasescanbeeasilyidenpatesinthechoiceofinvestmentproducts. considerthepossibilityofauser-clientpartnership,wheretheuserpartici- touseruleinductionorcase-basedreasoning.ruleinductionisappropriate CLIPS5.1waschosenasthemostsuitabletoolforimplementation,becauseCLIPS Onthebasisoftheresultsoftheprobingquestions,theexpertsystemshell tied.case-basedreasoningisappropriate,becausethereisavastcollection ofportfoliosthathavebeendevelopedovertheyearsanditshouldbeeasily possibletoextractthemostinuentialfeaturesfromthese. 15

17 6TheNecessitytoIterateKnowledgeAcquisition,AnalysisandDesign forforward-chaining,andclipswasreadilyavailable. allowsknowledgetoberepresentedasrulesandframes,clips'rulesaredesigned emphasis,withdesignbeingheavilybasedontheresultsoftheknowledgeanalysis, andimplementationbeingdependentontheexistenceofakbsdesign. Conventionalsystemdevelopmentnormallyexpectssoftwaredevelopmenttofollow alinearprocess,wheretheanalysisstageiscompletedbeforedesignisstarted,and thedesignstageiscompletedbeforeimplementationstage.kadshasasimilar sonalnancialplanning,severalproblemsarosewhichmadeitnecessarytoreturn tothestagesofknowledgeacquisitionandanalysisinordertorenethemodelsof analysedknowledge.thethreemainproblemswhicharosewere: Problemsregardingtheaccuracyofthetaskmodel:Itturnedoutthatthe However,duringtheimplementationofthisprototypeexpertsystemforper- taskmodelhadbeenincorrectandshouldreallyreadas: Beginbyobtaininginitialinformationfromtheclient Decomposethechosenskeletalinvestmentmodelintoasequence Goalassistaprivateinvestorindesigningacustomisedportfolio theclient'srequirements Taskdesign-investment-portfolio-for-client Selectfromtheinvestmentmodelsetthemodelthatbestmeets offunctionalcomponents Specifyeachcomponentsdesignprocedure Composeandlinkthefunctionalcomponentstoformaprovisional Foreachfunctionalcomponent versionoftheinvestmentportfolio,herebypayingattentiontothe Whilecurrentfunctionalcomponentisnotfullydesigned Specifyonepartoftherelevantfunctionalcomponent'sdesignprocedurtentiontoclientrequirements client'srequirementstoobtainthenalversionofinvestmentportfolio skeletalmodel Matchtheprovisionalversionoftheinvestmentmodelwiththe Designthepartspecied,herebypayingspecialat- 16

18 Problemsregardingthebestproductchoice:Theproductsintheinvestment Inotherwords,thetaskmodelwaschangedtoreectthefactthattheexpert speciesanddesignsonesub-componentbeforeshegoesontospecifyand designthenextsub-component. Figure6:RevisedTaskStructurefordesigninganinvestment categorylifeinsuranceareallcharacterisedbyleavingitlargelyuptothe portfolio Problemsregardingthesetofinvestmentmodels:Theemergenceofincreasingsimilaritiesbetweenthethreeincome-relatedmodels(theincomemodel, betweenspecicproducts. clienthowmuchincomehewantstowithdrawfromthem.thishighdegree Anewslot,purpose,wasneededtomakeaninformedchoicewhenchoosing ofexibilitymadeitdiculttodierentiatebetweenthedierentproducts. themixedmodel,andthehighincomemixedmodel)calledforareviewof versionofthespiralmodelofexpertsystemdevelopmentproposedby[9](seefigure approachtokbsdevelopment.thiscanbeillustratedusingaslightlymodied 7).5AsFigure7shows,themodiedspiralmodelassumesthatonepassthrough ThebestwaytodescribethisiterationistoviewitasaKADS-guidedspiral allthreemodelswereneeded,asthemotivationunderlyingeachmodelwas thevalidityofeachmodel.inthenalanalysis,however,itwasdecidedthat thestagesofknowledgeacquisition,knowledgeanalysis,designandimplementation fundamentallydierentandmadeuseofdierentheuristics. mainreasons: maynotbesucient.rather,asecond,andpossiblymorepassesmayberequired. 1.Incontrastto\rapidprototyping"methodsforKBSdevelopmentwhichare Thenecessityforthisloopinsystemdevelopmentaroseforthefollowingtwo basedongenericinterpretationmodels.whileatop-downapproachhasmany empiricalandinherentlyworkbottom-up,kadstakesatop-downapproach glectingand/oroverlookingimportantlow-levelknowledgeontherstpass, advantagesforguidanceandstructuring,ithastheinherentdangerofne- whichexplicitlylinksthedomainandinferencelevelsofthemodelofexpertise.see[14]fora needforthisapproach. awayfromalinearapproachtokbsdevelopmenttowardsaspiralapproachtokbsproject management{see[3].theresultsofthispaperprovideoneoftherstempiricalexamplesofthe 5ThesuccessortotheKADSmethodology,knownasCommonKADS,recommendsmoving 6Again,CommonKADSisaddressingthisarea,byintroducinganabstractdomainmodel andoffailingtoidentifyhowlow-levelknowledgeinteractswithhigher-level workedexample. decisions.6 17

19 2.Thedomainknowledgewasmorecomplexthanexpected.Inparticular,the declarativeknowledgeinthedomainofpersonalnancialplanningturned outtobelessstructuredthanexpected,andtheproceduralknowledgeinthe domainofnancialplanningturnedouttobemorecomplexandsophisticatedthanexpected.thetaskofdesignwasalsomademorecomplexbyby portfolio. thevariabilityinboththenumberandsizeofthecomponentsofatypical 18

20 human knowledge Knowledge Acquisition Knowledge Analysis real abstraction world models aroseduringimplementationwereresolved,andsystemdevelopmentthensmoothly Figure7:KADS-guidedSpiralModelofExpertSystemDevelopment couldwellbeguidedbyfurtherpassesthroughthestagesofknowledgeacquisition, proceededwithdesignandtheimplementationoftheprototypesystem.similarly, analysis,design,andimplementation,guidedbythespiralmodel. tem,andthemaintenanceofthehighlychangeableknowledgebaseofthesystem theprogressionoftheprototypesystemintoafully-edgedknowledge-basedsys- Inthesecondpassthroughthespiraldevelopmentprocess,theproblemsthat Implementation Design trary,theuseofkadsmodelshelpedtohighlightthoseareaswhereiterationis unexpected,itdoesnotnegatethevalidityandusefulnessofkads.onthecon- Thereforeitisworthnotingthatwhilethisloopinsystemdevelopmentwas computer program assistapotentialprivateinvestorinselectingaprofessionallybalancedmixtureof aprototypeknowledge-basedsystemforpersonalnancialplanningwhichwould necessary. investmentproductsthatwouldmeetalltheinvestor'srequirementswithregard 7Conclusions Asmentionedintheintroduction,theinitialaimoftheprojectwastodevelop PragmaticKADSmethodology. totheinvestment.thedevelopmentofthisprototypewastobeguidedbythe 19

21 implemented,whilstthegrowthmodelwasnotimplemented.theprototypesystem asitstandsisfullyfunctional,butcouldbeextendedinseveralways,inparticular bytheincorporationofagrowthportfolio; implemented.duetotimerestrictionsonlythethreeincome-relatedmodelswere Onthepracticalside,theprototypeexpertsystemfornancialplanningwas beguidedbytheuseofpragmatickads.ithasbeenshownthatthecontributionofpragmatickadswasmostinuentialandpervasiveduringtheknowledge extensionsregardingthestaticdomainknowledgeinformofspecicinvest- Onthetheoreticalside,thedevelopmentoftheprototypeexpertsystemwasto mentproducts. subsequenttotheinvestment; amorecomprehensivetreatmentoftheclient'snancialsituationpriorand implementationtechniques. Dolins'probingquestionscontributedgreatlytoselectingthemostappropriateAI designandimplementationstages.duringbehaviouraldesign,theuseofklineand servedasausefulcommunicationtoolintheinterviewswiththeexpert.during acquisitionandanalysisstages.duringknowledgeacquisition,thekadsmodels ofthesystemtobedevelopedandhadadecisive,thoughindirect,impactonthe knowledgeanalysis,themodelofexpertiselaidthefoundationsforthestructure consistentandcorrectimplementation. KBSdevelopers.Itsgreateststrengthslieintheprovisionofastructurewhichcan beusedasastartingpointforsystemdevelopment;intheseparationofdierent knowledgeacquisitionandknowledgeanalysiswasneededtoarriveatacomplete, initiallyexpected,thekadsmodelshelpedtohighlightthoseareaswheremore PragmaticKADSisthereforeconsideredtobeavaluabletoolinthehandsof Althoughthedevelopmentofthesystemdidnotproceedinthelinearway priateforthisproject;andguidanceonthedesignstagecouldusefullybedeveloped further. municationwithanexpert.ontheothersideofthecoin,kadsleanstowardsa sequentialmodelofkbsanalysis,designandimplementation,whichwasinappro- typesofknowledgeintodierentmodels;andintheuseofthesemodelsforcom- renementstosomeofthemodels.see[23]fordetails. derdevelopmentatthetimeofwriting,andisexpectedtoproduceconsiderable guidanceondierentapproachestomodeldevelopment,aswellasrecommending ItshouldbenotedthatCommonKADS,thesuccessortoKADS,wasstillun- 20

22 References Andrews,B.(June1989).SuccessfulExpertSystems.InFinancialTimes Burton,A.M.,Shadbolt,N.R.,Rugg,G.andHedgecock,A.P.(1988).KnowledgeElicitationTechniquesinClassicationDomains.InProceedings ofecai-88:the8theuropeanconferenceonarticialintelligence. IIFrameworkforKBSProjectManagement.ESPRITProjectP5248 Anon.(June1987).APEXchangestack.ExpertSystemsUser,2,11:5. Bright,C.,Martil,R.,Williams,D.andRajan,T.(1991).TheKADS- BusinessInformation,pages49{50. Decio,E.,Spampinato,L.anddiPasquale,S.(June1988).PECUNIA: anexpertportfolioadvisor.inproceedingsofthe8thinternational KADS-II,LloydsRegister. Feigenbaum,E.,McCorduck,P.andNii,P.(1988).TheRiseoftheExpert Dirks,S.(Sept1993).Developmentofaknowledge-basedsystemforpersonalnancialplanning.UnpublishedM.Sc.thesis,DeptofArticial Avignon. conferenceonexpertsystemsandtheirapplications,pages451{461, Company.Macmillan. Intelligence,UniversityofEdinburgh. Guilfoyle,C.andJecoate,J.(February1988).InExpertSystemsinBanking Gammack,J.G.(1987).Dierenttechniquesanddierentaspectsondeclarativeknowledge.InKidd,A.L.,(ed.),KnowledgeAcquisitionforExpert Giarratano,J.andRiley,G.(1989).ExpertSystems-PrinciplesandProgramming.PWS-KentPublishingCompany. &Securities,page156.Ovum. Humpert,B.andHolley,P.(May1988).ExpertSystemsinnanceplanning. Systems.PlenumPress. Kingston,J.K.C.(1993a).PragmaticKADS1.0.TechnicalReportAIAI- Kindle,K.,Cann,R.,Craig,M.andMartin,T.(1989).PFPS:Personal ExpertSystems,5,2:79. Kingston,J.K.C.(1993b).Re-engineeringIMPRESSandX-MATEusing FinancialPlanningSystem.InInnovativeApplicationsofArticialIntelligence,pages51{61.AAAI. IR-13,AIAI,UniversityofEdinburgh. CommonKADS.InExpertSystems93.BritishComputerSociety,CambridgeUniversityPress. 21

23 Kingston,J.K.C.(1994).DesignbyExploration:AProposedCommonKADS Kline,P.J.andDolins,S.B.(1989).Designingexpertsystems:aguideto Komahashi,K.(1989).Japanesewisdomgetselectric.BestofBusiness InferenceStructure.Submittedto`KnowledgeAcquisition'. selectingimplementationtechniques.wiley. MacNee,C.(Sept1992).PDQ:Aknowledge-basedsystemtohelpknowledgebasedsystemdesignerstoselectknowledgerepresentationandinference Kuipers,B.andKassirer,J.P.(1987).Knowledgeacquisitionbyanalysis International,pages32{37. ofverbatimprotocols.inkidd,a.l.,(ed.),knowledgeacquisitionfor Press. ExpertSystems:APracticalHandbook,chapter3,pages45{71.Plenum Schreiber,A.Th.,Wielinga,B.J.andBreuker,J.A.,(eds.).(1993).KADS: Smart,J.(April1993).HARDY.Airing,15:3{7.AIAI,UniversityofEdinburgh. techniques.unpublishedm.sc.thesis,deptofarticialintelligence, UniversityofEdinburgh. demicpress,london. APrincipledApproachtoKnowledge-BasedSystemDevelopment.Aca- Wielinga,R.(October1993).ExpertiseModel:ModelDenitionDocument. Thomczyk,C.(March1991).Knowledge-basedAssetStructureAnalysis.In Industry.UniversitaCattolica,Milan. AnAnalysisofExpertSystemsApplicationsintheEuropeanBanking CommonKADSProjectReport,UniversityofAmsterdam,KADS-II/M2/UvA/026/2.0. Wielinga,R.,vandeVelde,W.,Schreiber,G.andAkkermans,H.(Jun1993). UniversityofAmsterdam. ExpertiseModelDenitionDocument.CommonKADSProjectReport, 22

24 Investment Portfolio is-part-of is-part-of is-part-of Emergency Fund Income Fund Growth Fund is-a is-a is-a is-part-of is-part-of bank account building society account life insurance safe growth fund pure growth fund instant access acount National Savings is-part-of is-part-of is-part-of notice account National Savings income bond low risk pure growth fund medium risk pure growth fund high risk pure growth fund National Savings investment account unit trusts high interest cheque account back-to-back arrangements investment trusts investment bonds gilts with-profit bonds annuities FIRST option bond capital bond series D shares business expansion schemes 5th issue index-linked certificate 37th issue savings certificate discretionary managment funds off-shore funds TESSA account 23

25 Repairing SYSTEM MODIFICATION Controlling Maintaining Remedying Prediction of behaviour Diagnosis SYSTEM ANALYSIS Prediction Prediction of values Classification Simple classification Identifying Monitoring Assessment Transformation Explorationbased design SYSTEM SYNTHESIS Design Transformational design Refinement design Single stream refinemt design Planning Hierarchical design Multiple stream refinemt design Modelling 24 Configuration

26 Model Set select Functional Specification Skeletal Model decompose Functional Components specify Functional Specification design Design Model 25 compose Composed Model match Design Model

27 set of 4 investment models select client-specific constraints skeletal investment model decompose sequence of functional components of chosen model specify procedural design specification for each functional component design design models for each functional component compose provisional design model of investment portfolio match final design model of investment portfolio 26

28 References [3]C.Bright,R.Martil,D.Williams,andT.Rajan.TheKADS-IIFrameworkfor [2]Anon.APEXchangestack.ExpertSystemsUser,2,11:5,June1987. [1]B.Andrews.SuccessfulExpertSystems.InFinancialTimesBusinessInformation,pages49{50,June1989. KBSProjectManagement.ESPRITProjectP5248KADS-II,LloydsRegister, [5]E.Decio,L.Spampinato,andS.diPasquale.PECUNIA:anexpertportfolio [4]A.M.Burton,N.R.Shadbolt,G.Rugg,andA.P.Hedgecock.KnowledgeElicitationTechniquesinClassicationDomains.InProceedingsofECAI-88:The [6]S.Dirks.Developmentofaknowledge-basedsystemforpersonalnancialplanning.Master'sthesis,DeptofArticialIntelligence,UniversityofEdinburgh, andtheirapplications,pages451{461,avignon,june1988. advisor.inproceedingsofthe8thinternationalconferenceonexpertsystems 8thEuropeanConferenceonArticialIntelligence,1988. [7]E.Feigenbaum,P.McCorduck,andP.Nii.TheRiseoftheExpertCompany. Sept1993. [9]J.GiarratanoandG.Riley.ExpertSystems-PrinciplesandProgramming. [8]J.G.Gammack.Dierenttechniquesanddierentaspectsondeclarative PlenumPress,1987. knowledge.ina.l.kidd,editor,knowledgeacquisitionforexpertsystems. PWS-KentPublishingCompany,1989.Agoodintroductorytextwithapracticalapproach,whichalsosuppliesadiskoftheCLIPSprogrammingtool,and amanualontheuseofclips. Macmillan,1988. [10]C.GuilfoyleandJ.Jecoate.InExpertSystemsinBanking&Securities,page [11]B.HumpertandP.Holley.ExpertSystemsinnanceplanning.ExpertSystems,5,2:79,May {61.AAAI,1989. PlanningSystem.InInnovativeApplicationsofArticialIntelligence,pages [12]K.Kindle,R.Cann,M.Craig,andT.Martin.PFPS:PersonalFinancial 156.Ovum,February

29 [13]J.K.C.Kingston.PragmaticKADS1.0.TechnicalReportAIAI-IR-13,AIAI, [14]J.K.C. [15]J.K.C.Kingston.DesignbyExploration:AProposedCommonKADSInferenceStructure.Submittedto`KnowledgeAcquisition',1994. Kingston. UniversityofEdinburgh,1993. Re-engineeringIMPRESSandX-MATEusingCommonKADS.InResearch anddevelopmentinexpertsystemsx,pages17{42.cambridgeuniversity Press, [16]P.J.KlineandS.B.Dolins.Designingexpertsystems:aguidetoselecting [17]K.Komahashi.Japanesewisdomgetselectric.BestofBusinessInternational, [18]B.KuipersandJ.P.Kassirer.Knowledgeacquisitionbyanalysisofverbatim implementationtechniques.wiley,1989. [19]CMacNee.PDQ:Aknowledge-basedsystemtohelpknowledge-basedsystem pages32{37,1989. [20]A.Th.Schreiber,B.J.Wielinga,andJ.A.Breuker,editors.KADS:APrincipledApproachtoKnowledge-BasedSystemDevelopment.AcademicPress, London,1993. designerstoselectknowledgerepresentationandinferencetechniques.master's protocols.ina.l.kidd,editor,knowledgeacquisitionforexpertsystems:a PracticalHandbook,chapter3,pages45{71.PlenumPress,1987. [21]J.Smart.HARDY.Airing,15:3{7,April1993.AIAI,UniversityofEdinburgh. thesis,deptofarticialintelligence,universityofedinburgh,september1992. [22]C.Thomczyk.Knowledge-basedAssetStructureAnalysis.InAnAnalysis [24]B.Wielinga,W.vandeVelde,G.Schreiber,andH.Akkermans.Expertise [23]B.Wielinga.ExpertiseModel:ModelDenitionDocument.Com- II/M2/UvA/026/2.0. Cattolica,Milan,March1991. monkadsprojectreport,universityofamsterdam,october1993.kads- ofexpertsystemsapplicationsintheeuropeanbankingindustry.universita Amsterdam,Jun1993. ModelDenitionDocument.CommonKADSProjectReport,Universityof 28