?Copyright2016.MercuryLearningandInformation.Allrightsreserved.ArtificialIntelligenceinthe21stCentury

S.Lucci/D.Kopec

Chapter1:OverviewofArtificial

Intelligence1?Copyright2016.MercuryLearningandInformation.Allrightsreserved.OverviewofArtificialIntelligence

1.0Introduction1.1TheTuringTest1.2StrongAIversusWeakAI1.3Heuristics1.4IdentifyingProblemsSuitableforAI1.5ApplicationsandMethods1.6EarlyHistoryofAI1.7RecentHistoryofAItothePresent1.8AIintheNewMillennium2?Copyright2016.MercuryLearningandInformation.Allrightsreserved.Introduction.Thischapterexploresthefundamentalissues,topics,areas,andquestionswhicharetypicallyassociatedwithartificialintelligence.3Introduction/cont.

Artificial–usuallyhasanegativeconnotation

(synthetic–i.e.manmade)

e.g.artificialflowerlook…maybe feel ...no smell...no

artificiallight

naturallightelectriclight sunlightcandleskerosene

?Copyright2016.MercuryLearningandInformation.Allrightsreserved.4Introduction/cont.artificialmotion

naturalmotionplanes walkingtrains horseautomobiles?Copyright2016.MercuryLearningandInformation.Allrightsreserved.5IntelligenceIntelligenceistheabilityofanindividualtolearnfromexperience,toreasonwell,torememberimportantinformation,andtocopewiththedemandsofdailyliving.Intelligencemaybedefinedbroadlyasthefacilityatsolvingproblems.?Copyright2016.MercuryLearningandInformation.Allrightsreserved.6?Copyright2016.MercuryLearningandInformation.Allrightsreserved.SequenceProblems.1, 3,6, 10, 15, 21, ? 28isnextTriangularnumbersnthentry=e.g.2ndtriangular#=1, 2,2, 3,3,3,4,4, 4,4, ?2, 3,3,5, 5,5,7,7, 7,7, ?

0, 1,2, ? 3…notsofast!

7SequenceProblems/cont.Anotherpossibility…

0 = 0 1! = 1 2!! = (2!)!=(2x1)!=2!=2 3!!! = (3!)!!=((3x2)!)!=(6!)!=720!

Andfinally…9, 14,23, ??Copyright2016.MercuryLearningandInformation.Allrightsreserved.8?Copyright2016.MercuryLearningandInformation.Allrightsreserved.BuildingIntelligentSystems

KnowledgeRepresentationSearchLearning

KnowledgeRepresentation

-Productionrules …ifcondthenresult-Logic-Frames -Scripts-Semanticnetworks

9BuildingIntelligentSystems/cont.Framesandscriptsutilizetheprototypicalnatureofmostevents,e.g.visitstoarestaurant,

dentist,etc.

ConceptMaps,ConceptualGraphs,Agents?Copyright2016.MercuryLearningandInformation.Allrightsreserved.10?Copyright2016.MercuryLearningandInformation.Allrightsreserved.SearchBlindsearch–noknowledgeofproblemdomain

Depthfirstsearch(dfs) A,B,D,E,C,F,GBreadthfirstsearch(bfs)A,B,C,D,E,F,GHeuristicsearch–employestimatesofcloseness

to

goal.

11?Copyright2016.MercuryLearningandInformation.Allrightsreserved.Learning–improvedperformanceviapractice

Paradigms–connectionist/artificialneuralnetworks(ANN)e.g.learningaBooleanfunction–patternclassification

two-inputANDfunction

12Learning–improvedperformanceviapractice

FeatureextractionHowwouldyouteachthistoachild?Rewardwhencorrect,“punish”whenwrong.SUPERVISEDLEARNINGThisscalesupmaleorfemale?Whatarefeatureshere??Copyright2016.MercuryLearningandInformation.Allrightsreserved.13?Copyright2016.MercuryLearningandInformation.Allrightsreserved.EvolutionaryComputationCharlesDarwin–Britishnaturalist

“Ihavecalledthisprinciple,bywhicheachslight

variation,ifuseful,ispreserved,bythetermnaturalselection”–CharlesDarwinfrom“TheOriginofSpecies”,1859

14?Copyright2016.MercuryLearningandInformation.Allrightsreserved.EvolutionaryComputation

“Darwin’stheoryofevolutionaryselectionholdsthatvariationwithinspeciesoccursrandomlyandthatthesurvivalorextinctionofeachorganismisdeterminedbythatorganism’sabilitytoadapttoitsenvironment.”

/lucidate/librarySurvivalofthefittestNaturalselectionoccursinnatureatarateofthousandsormillionsofyears.Insideacomputer–evolutionproceedssomewhatfaster.15?Copyright2016.MercuryLearningandInformation.Allrightsreserved.

GeneticAlgorithms

TheproblemisencodedasastringExample: 3-puzzleStartState Goal

Operators…whereweassumeitistheblankthatmovesEncodetheseoperatorsasbinarystrings…Forexample,

00011011

16?Copyright2016.MercuryLearningandInformation.Allrightsreserved.

GeneticAlgorithms/cont.Asolutionforthispuzzle(whenoneexists)consistsofaseriesofmoves.Suchasolution(whethersuccessfulornotso)maythusberepresentedbyabinarystring.Forexample,thestring:001101correspondsto:

17GeneticAlgorithms/cont.?Copyright2016.MercuryLearningandInformation.Allrightsreserved.Toeachsuchstringweshallattachafitnessfunction.

Whatmetricwouldyoupropose?WewilldiscussGeneticAlgorithmslaterinthistext//we’regettingclose!18?Copyright2016.MercuryLearningandInformation.Allrightsreserved.

ReturningtotheissueofIntelligence…

Howdoesonedecideifsomeone(something?)isintelligent?Areanimalsintelligent? Dogs? Cats? Ants? Dolphins?Andifso,howwouldonemeasureit?…

CleverHans–Berlin,circa1900Ahorsethatknewhowtodomath…ordidit?19Intelligence

Intelligenceisthecharacteristicalmostuniversallyagreeduponassettinghumansapartfrom(andabove?)othercreatures.

Thedeclaredgoalofartificialintelligenceresearchistoteachmachinesto“think”,i.e.todisplaythosecharacteristicsusuallyassociatedwithhumanintelligence.?Copyright2016.MercuryLearningandInformation.Allrightsreserved.20?Copyright2016.MercuryLearningandInformation.Allrightsreserved.

CanMachinesThink?

Notaneatyesorno,butratherahighlyqualified“toacertainextentunderspecialconditions.”Doesaperson,animal,machinepossessintelligence…theanswerisnotbinary: Somepeoplearesmarterthanothers Someanimalsaresmarterthanothers

Turingrephrasedthisquestioninoperationalterms.i.e.hesoughttoseparate

functionalityfrom

implementation.(analogywithAbstractDataTypes–ADT)21?Copyright2016.MercuryLearningandInformation.Allrightsreserved.MeasuringIntelligenceAlanTuring(1950)proposedtwoimitationgamesInthefirst:-Aseriesofquestionsisasked.-Interrogatormustdeterminegenderofpersonontheotherside-Ifamanissuccessfulindeceivingtheinterrogator,thenwesaythathehaspassedthisimitationgameWhatquestionswouldyousuggest?22?Copyright2016.MercuryLearningandInformation.Allrightsreserved.

Thesecond… TheTuringTestforIntelligence.

LoebnerPrizeof$100,000

Isitacomputerorahuman?IfthecomputerissuccessfulindeceivingtheinterrogatorthenwesaythatithaspassedtheTuringTest.

23?Copyright2016.MercuryLearningandInformation.Allrightsreserved.TheTuringTest/cont.

ProposedQuestions:Sqrt(1000017)=?…notagoodidea,whynot?Areyouafraidofdying?Howdoesthedarkmakeyoufeel?Whatdoesitfeelliketobeinlove?Isthisavalidbarometerforintelligence?24?Copyright2016.MercuryLearningandInformation.Allrightsreserved.Block’sCriticismoftheTuringTest

EnglishtextisencodedinASCII

Henceaseriesofquestionsandanswersmaybestoredasa(verylarge)number.

OnecouldenvisionmanyinstancesoftheTuringTestbeingstoredonaverylargedatabase.

Passingthetestcouldthenbeaccomplishedbytablelookup.Granted,suchacomputersystemdoesnotexistatpresent…

Butifitdid,wouldyoufeelcomfortableincallingthiscomputerintelligent?

25?Copyright2016.MercuryLearningandInformation.Allrightsreserved.

Searle’sCriticismoftheTuringTest

TheChineseRoomwehaveaninterrogatorwhowillaskquestions–thistime-inChinese.-wehaveanindividualwhodoesnotknowChinese;thatpersonpossessesaverydetailed“rulebook.”tomostpeoplewhodonotknowChinese,thelanguageappearsassquiggles.

26Searle’sCriticismoftheTuringTest/cont.DoesthispersonknowChinese?

去卡內基音樂廳該怎麼走

("HowdoIgettoCarnegieHall?"

)

WhatistheanalogywiththeTuringTest??Copyright2016.MercuryLearningandInformation.Allrightsreserved.27?Copyright2016.MercuryLearningandInformation.Allrightsreserved.TheChineseRoom.

Nowenvisioninsteadofasinglepersonwitharulebook,awholegymnasiumofpeoplewith“notes”thatarepassedtooneanother.

DoesthegymnasiumknowChinese?…28TheChineseRoom/cont.?Copyright2016.MercuryLearningandInformation.Allrightsreserved.

OK–finallypicturethebrainofsomeonewhoindeedknowsChinese.DoesanindividualneuronknowChinese?Whatofacollectionoftheseneurons?WheredoestheknowledgeofChinesereside?29?Copyright2016.MercuryLearningandInformation.Allrightsreserved.Functionalityvs.ImplementationTuringwastryingtoseparatehowsomethingworksfromhowitcanbebuilt.

e.g.functionalityofacar: -steponthebrake-thecarshouldstop. -steponthegas-thecarshouldmove. -turnthesteeringwheelleft…

Implementation-meanwhileanautomotivefactorymustknowaboutengines,brakeliningsandtransmissions

30?Copyright2016.MercuryLearningandInformation.Allrightsreserved.DefenseofTuringPremise:Itisnotpossibletogaininsightontheinternalstateofsomethingfromexternalobservations.Rutherfordwasabletodeducetheinternalstateofmatter–mostlyspace(beforeelectronmicroscope)Matterhighenergyparticles31?Copyright2016.MercuryLearningandInformation.Allrightsreserved.StrongAIvs.WeakAIStrongAIisthebeliefthatprovidingacomputerwithintelligentsoftwaresomehowenablesthatmachinetothink.Anditwillpossessconsciousness(asenseof‘I’)muchashumansdo.

Hollywoodhaslongbeenaproponentofthisviewpoint,e.g.themovie“AI”inwhichtheandroidmaincharacteryearnstohavehisidentityacknowledged.32StrongAIvs.WeakAI/cont.WeakAI:Intelligentbehaviorcanbemodeledandusedbycomputerstosolvecomplexproblems.

Nopresuppositionismadethatthecomputerisintelligentinthewaythatahumanis.Mostartificialintelligenceresearcherssubscribetothisbelief.

?Copyright2016.MercuryLearningandInformation.Allrightsreserved.33?Copyright2016.MercuryLearningandInformation.Allrightsreserved.StrongMethodsvs.WeakMethodsWeakMethods:employsystemssuchaslogic,automatedreasoning,andothergeneralstructuresthatcanbeappliedtoawiderangeofproblems;donotincorporateanyrealknowledgeabouttheworldandtheproblemthatisbeingsolved.34StrongMethodsvs.WeakMethods

StrongMethods:dependonasystembeinggivenagreatdealofknowledgeaboutitsworldandtheproblemsthatitmightencounter

Example:ExpertSystemswiththeirstrongrelianceondomainknowledge.

Note:Thestrongvs.weakmethodsdichotomy

shouldnotbeconfusedwiththedistinctionbetweenstrongandweakAI.?Copyright2016.MercuryLearningandInformation.Allrightsreserved.35?Copyright2016.MercuryLearningandInformation.Allrightsreserved.Heuristics

Aheuristicisa“aruleofthumb”forsolvingaproblem.Thisistobecontrastedwithanalgorithmwhichisadefinite,effectiveprocedureguaranteedtosolveaproblem.Aheuristicmaybehelpfulinsolvingaproblembutitdoesnotguaranteeasolution.

36HeuristicExample.Example1:Whatisthediagonalofarectangularsolid?…

TheHeuristicemployed:Solveasimplerbutrelatedproblem.Youmaytherebygaininsightintotheoriginalproblem?Copyright2016.MercuryLearningandInformation.Allrightsreserved.37?Copyright2016.MercuryLearningandInformation.Allrightsreserved.Heuristics/cont.38?Copyright2016.MercuryLearningandInformation.Allrightsreserved.ASecondHeuristicHowcanyoufillexactly12quartsofwaterwhenyouhaveonlytwocontainers,aneightquartpailandaneighteenquartpail?

Onecouldusetrial-and-errorandjusthopeforthebest.39?Copyright2016.MercuryLearningandInformation.Allrightsreserved.ASecondHeuristic/cont.

Instead,Polyasuggeststheheuristicofstartingwiththegoalstateandworkingbackwards.40ASecondHeuristic/cont.

Workingbackwardtosolvethe12-QuartProblem.Patha,b,ctakesusfromthedesiredgoalstatetotheinitialstate.Toactuallysolvetheproblem,wewouldreversetheorder.

?Copyright2016.MercuryLearningandInformation.Allrightsreserved.41?Copyright2016.MercuryLearningandInformation.Allrightsreserved.AnAfterword

Problemsolvingviaheuristicsisanexampleofaweakmethod.HeuristicmethodswerepopularintheearlydaysofAI–the1950’sandintothe1960’s.StrongmethodsrepresentedaparadigmshiftinA.I.intheearly1970’swiththeadventofExpertSystems;therewasanemphasisontheimportanceofknowledgeinproblemsolving.42AnAfterword/cont.AnExpertSystem(E.S.)possesses(someof)theexpertiseofahumanexpertinalimiteddomain.MYCIN,anearly(andprobablybestknownE.S.)-wascapableofdiagnosingbacterialinfections.?Copyright2016.MercuryLearningandInformation.Allrightsreserved.43?Copyright2016.MercuryLearningandInformation.Allrightsreserved.AgentsAnagentisanentitythatiscapableofperceivingitsenvironmentandrespondingappropriatelytoit.

Iftheagentisintelligent,itshouldbeabletoweighalternatives.

Thisagentshouldbeabletoderivenewinformationfromdatabyapplyingsoundlogicalrules.

Itshouldpossessextensiveknowledgeinthedomainwhereitisexpectedtosolveproblems.

44ApplicationAreas/cont.WeexpecttocommunicatewiththisagentinanaturallanguagesuchasEnglishorChinese.?Copyright2016.MercuryLearningandInformation.Allrightsreserved.45ApplicationAreas/cont.HencethefollowingA.I.applicationareashavereceivedmuchinterest:

GamePlayingandPuzzlesAutomatedReasoningExpertSystemsLanguageUnderstanding?Copyright2016.MercuryLearningandInformation.Allrightsreserved.46?Copyright2016.MercuryLearningandInformation.Allrightsreserved.GamePlayingThe15-puzzle:15numbersarewrittenonsmallplasticsquaresandarearrangedwithinalargerplasticframe.Onepositionisleftblanksothatsmallertilesmayslideinasmanyasfourdirections.Anarbitraryarrangement.47GamePlaying/cont.Noticethatthe3isfreetomovedownandthe12canmovetotheright.Onlyonemovemayoccuratatime.?Copyright2016.MercuryLearningandInformation.Allrightsreserved.48?Copyright2016.MercuryLearningandInformation.Allrightsreserved.GamePlaying/cont.Smallerinstancesofthe15–puzzlearemoreconvenienttoworkwith.

The3–puzzleThe8-puzzle49GamePlaying/cont.Foreaseofpresentation,weconsiderthe3–puzzleinthefollowingexamples.Inthisclassofpuzzlesnumberedtilesmayslideinoneoffourdirections.Itismoreconvenient,however,toconsidertheblanktobemoving.Hence,ingeneral,theblankmaymoveinoneoffourdirections:

UpDown

RightLeft

?Copyright2016.MercuryLearningandInformation.Allrightsreserved.50?Copyright2016.MercuryLearningandInformation.Allrightsreserved.GamePlaying/cont.

Wearepresentedwithtwostatesofthispuzzle.One,thestartstateisarbitrary.Thesecond,thegoalstate,isalsoarbitrary,butisoftenchosenasthatarrangementwiththetiles‘inorder’.

StartStateGoalState51GamePlaying/cont.TheobjectofthispuzzleistogetfromtheStartStatetotheGoalState.Insomeinstances,asolutionwiththeminimumnumberofmovesissought.?Copyright2016.MercuryLearningandInformation.Allrightsreserved.52?Copyright2016.MercuryLearningandInformation.Allrightsreserved.GamePlaying/cont.TheuniverseofdiscourseforsuchproblemsiscalledtheStateSpaceTree.Itconsistsofallpossiblestatesofagivenproblem.

AStateSpaceTreewillbeatreewhoserootisthestartstateandoneofwhoseleavesisagoalstate.Branchesbetweenstatescorrespondtolegalmovesofthegame(orpuzzle)beingconsidered.

AportionoftheStateSpaceTreeforourinstanceofthe3-puzzle.53GamePlaying/cont.?Copyright2016.MercuryLearningandInformation.Allrightsreserved.Movesareexploredintheorder

ManynodesarerepeatedThistreemaybequitelargeevenforarelatively‘small’problem54?Copyright2016.MercuryLearningandInformation.Allrightsreserved.AutomatedReasoningPresentsthesoftwarewithacollectionoffacts

UsesdeductionExample:MichaelandLouiseachhaveajob.ThejobsarepostofficeclerkandFrenchprofessor.MichaelonlyspeaksEnglishandLouisholdsaPh.D.inFrench.55AutomatedReasoning/cont.ProductionrulesareusedasamethodofknowledgerepresentationGeneralForms: IF(condition)thenaction orIF(condition)thenfactUsedincreatingexpertsystemsAportionofanexpertsystemforautomobilediagnosis If(carwon'tstart)thencheckheadlights If(headlightswork)thencheckgasgauge If(gastankempty)thenaddgasolinetofueltank If(headlightsdon'twork)thencheckbattery?Copyright2016.MercuryLearningandInformation.Allrightsreserved.56?Copyright2016.MercuryLearningandInformation.Allrightsreserved.CellularAutomataMaybeviewedasacollectionofcellsin

n-dimensionalspace.Eachcellmaybeinanyoneofasmallnumberofstates,typicallytwo.CharacterizedbytwopropertiesPhysicaltopology:theshapeoftheCA,rectangularorhexagonal57CellularAutomata/cont.Updaterule:ruleusedtodeterminethenextstateofacellintermsofitspresentstateaswellasthestatesofitsneighboringcells.?Copyright2016.MercuryLearningandInformation.Allrightsreserved.58?Copyright2016.MercuryLearningandInformation.Allrightsreserved.UncertaintyReasoning.AIsystemsareplaguedwithuncertaintyChanceisaninimitablecomponentofourexistenceConsiderthefollowingsets:Setofpeoplewhoaresatisfiedwiththeirjob.Setofpeoplewhoareunsatisfiedwiththeirjob.ItisnotunusualforpeopletolovetheirjobandalsobeunsatisfiedYoucanconsiderthenthefuzzyset59?Copyright2016.MercuryLearningandInformation.Allrightsreserved.HistoryofAIDatesbacktoancientEgyptianswhobuiltstatuesthatcontainedhiddenprieststhatprovidedcounseltocitizens

Aristotleemphasizedtheabilityofpeopletoreason

BritishlogicianGeorgeBooleestablishedthesystemforexpressinglogicalexpressions--BooleanAlgebra60?Copyright2016.MercuryLearningandInformation.Allrightsreserved.LogicMachinesFirstlogicmachinewasbuiltbyCharlesStanhope(1753-1816)Best-knownandfirstprototypeofthemodern-daycomputerwasCharlesBabbage'sDifferenceEngine.TheAnalyticalEngine(successortotheDifferenceEngine,neverrealized)whichwouldbeabletoperformtasksthatrequirehumanthought,suchasgamesofskill–chess,checkers,etc.Babbage'sAnalyticalEngine61?Copyright2016.MercuryLearningandInformation.Allrightsreserved.LogicMachines/cont.TheNimotron,developedin1938byEdwardCondon,GeraldTwoneyandWillardDerr,wasthefirstmachinethatcouldplayacompletegameofskill

TheTurkdevelopedin1790byBaronvonKempelen.Asmallmaster-levelhumanchessplayerhidinsidethemachinefoolingpeopleintothinkingtheywereplayingagainstamachine

TorresyQuevedo(1852-1936)builtthefirstexpertsystem.ItplayedtheendgameKingandRookvsKinginchess.

62LogicMachines/cont.

KonradZusedevelopedcomputersbasedonvacuumtubesandelectro-mechanicalmemorycalledZ1,Z2,andZ3.TheZ3isthefirstreliable,freelyprogrammableworkingcomputerbasedonfloating-point.?Copyright2016.MercuryLearningandInformation.Allrightsreserved.63?Copyright2016.MercuryLearningandInformation.Allrightsreserved.GamesArthurSamueldevelopedaprogramtoplaycheckersbasedonatableof50heuristicsin1959.

RichardGreenblatt'sprogramwasthefirsttoplayclub-levelchess

ProgramscouldplayExpertlevelchess(top1%)bytheendofthe1970s.

KenThompson'sBellewasthefirstprogramtoofficallyachievetheMasterlevel.64Games/cont.HansBerliner’sHitechfromCarnegie-MellonUniversitywasthefirstSeniorMasterprogram.

Hsu,Campbell,etal.developedDeepThoughtfromCarnegie-MellonUniversitywhichbecamethefirstprogramtobeatGrandmastersonaregularbasis?Copyright2016.MercuryLearningandInformation.Allrightsreserved.65?Copyright2016.MercuryLearningandInformation.Allrightsreserved.Games/cont.DeepBlueplayedasix-gamematchwithWorldChampionGarryKasparovandlost4-2.

DeeperBlue(successortoDeepBlue)defeatedKasparov3.5-2.5in1997

JonathanSchaefferstartedwritingChinookin1989.

ChinooklosttoWorldCheckersChampionMarionTinsley4-2with34drawsin1992.

66Games/cont.The1994rematchendedafter6drawsduetoTinsley’spoorhealth.

In2007Checkerswas“weaklysolved”bySchaefferetal.?Copyright2016.MercuryLearningandInformation.Allrightsreserved.67?Copyright2016.MercuryLearningandInformation.Allrightsreserved.ExpertSystemsEarliestsystemwasDENDRAL.Itspurposewastoidentifyunknownchemicalcompoundsonthebasisoftheirmassspectrographs

MYCINwasdevelopedtofacilitatetheinvestigationofinfectiousblooddiseases.

Hadover400rulesUsedfortrainingresidentsatStanfordHospital

68ExpertSystems/cont.

XCON(some10,000rules)wasdevelopedtohelpconfigureelectricalboardsonVAXcomputers.Sincethe1980sthousandsofexpertsystemshavebeendeveloped.

Standalonesystemsandembeddedintoothersoftwaresystemsforcontrolpurposes.?Copyright2016.MercuryLearningandInformation.Allrightsreserved.69?Copyright2016.MercuryLearningandInformation.Allrightsreserved.AIintheNewMillenniumAImethodologieshavebeenabsorbedintotechnologiesforcomputerscienceExpertsystemsandsearchtechniquesthatspawnedfromAIresearcharenowusedinsystemssuchas

ALVINN–systemtocontrolavehicleFinancialdecisions–purchaseandsaleofstockWeb-basedagentssuchastheWorldWideWeb70?Copyright2016.MercuryLearningandInformation.Allrightsreserved.TheNext45YearsEventuallyintelligentsystemsthataresmall,unobtrusiveandembeddedwillbeabletopersevereandenhancepeople'smentalcapabilities.

Whatitmeanstobeahumanbeingmaybecomeapointofdiscussion

Wheredoesthepersonendandthemachinebegin,andviceversa?Reference:TheMovieBicentennialMan

RobinWilliams,JohnForsyth71KeyTermsagentalgorithmartificialartificialintelligence(AI)commonsenseheuristicintelligenceStrongAIWeakAIWorldknowledge?Copyright2016.MercuryLearningandInformation.Allrightsreserved.72SummaryThisChapterpresentsanoverviewofAI

ADiscussionofIntelligenceandsomeofthe

controversysurroundingaworkingdefinition–

includingthewell-knownTuringTest

Abriefhistoryofthefield–includingearlysystems

fromRomanTimestothepresent.

Earlyrelianceonheuristicstolateremphasison

knowledge?Copyright2016.MercuryLearningandInformation.Allrightsreserved.73Summary/cont.Theimportanceof: -KnowledgeRepresentation -Search -LearningSeveralsuccesseswerepresented:

-ExpertSystems

-Game-Playing

-NeuralNetworks

-GeneticAlgorithms?Copyright2016.MercuryLearningandInformation.Allrightsreserved.74ArtificialIntelligenceinthe21stCentury

S.Lucci/D.Kopec

Chapter2:

UninformedSearch?Copyright2016.MercuryLearningandInformation.Allrightsreserved.75?Copyright2016.MercuryLearningandInformation.Allrightsreserved.76Contents2.0

SearchinIntelligentSystems

2.1StateSpaceGraphs

2.2GenerateandTestParadigm

2.3BlindSearchAlgorithms

2.4ImplementingandComparingBlindSearchAlgorithms

Summary?Copyright2016.MercuryLearningandInformation.Allrightsreserved.77SearchinIntelligentSystems

Searchisanaturalpartofpeople’slives

Softwarethatsolvessearchproblemsfasteraredeemedtobemoreintelligent?Copyright2016.MercuryLearningandInformation.Allrightsreserved.782.1StateSpaceGraphsAmathematicalstructurethathelpstoformalizethesearchprocess

Possiblealternativepathsleadingtoasolutioncanbeexploredandanalyzed

Asoluti