《信息科學類專業(yè)英語》課件第21章_第1頁
《信息科學類專業(yè)英語》課件第21章_第2頁
《信息科學類專業(yè)英語》課件第21章_第3頁
《信息科學類專業(yè)英語》課件第21章_第4頁
《信息科學類專業(yè)英語》課件第21章_第5頁
已閱讀5頁,還剩40頁未讀, 繼續(xù)免費閱讀

下載本文檔

版權說明:本文檔由用戶提供并上傳,收益歸屬內容提供方,若內容存在侵權,請進行舉報或認領

文檔簡介

Lesson21IntroductiontoArtificialIntelligence

(第二十一課現代人工智能簡介)

Vocabulary(詞匯)ImportantSentences(重點句)Multiple-choiceQuestions(多選題)Problems(問題)

HumankindhasgivenitselfthescientificnameHomosapiens—manthewise—becauseourmentalcapacitiesaresoimportanttooureverydaylivesandoursenseofself.Thefieldofartificialintelligence,orAI,attemptstounderstandintelligententities.Thus,onereasontostudyitistolearnmoreaboutourselves.Butunlikephilosophyandpsychology,whicharealsoconcernedwithintelligence,AIstrivestobuildintelligententitiesaswellasunderstandthem.AnotherreasontostudyAIisthattheseconstructedintelligententitiesareinterestingandusefulintheirownright.AIhasproducedmanysignificantandimpressiveproductsevenatthisearlystageinitsdevelopment.Althoughnoonecanpredictthefutureindetail,itisclearthatcomputerswithhuman-levelintelligence(orbetter)wouldhaveahugeimpactonoureverydaylivesandonthefuturecourseofcivilization.[1]

AIaddressesoneoftheultimatepuzzles.Howisitpossibleforaslow,tinybrain,whetherbiologicalorelectronic,toperceive,understand,predict,andmanipulateaworldfarlargerandmorecomplicatedthanitself?Howdowegoaboutmakingsomethingwiththoseproperties?Thesearehardquestions,butunlikethesearchforfaster-than-lighttraveloranantigravitydevice,theresearcherinAIhassolidevidencethatthequestispossible.Alltheresearcherhastodoislookinthemirrortoseeanexampleofanintelligentsystem.

AIisoneofthenewestdisciplines.Itwasformallyinitiatedin1956,whenthenamewascoined,althoughatthatpointworkhadbeenunderwayforaboutfiveyears.Alongwithmoderngenetics,itisregularlycitedasthe“fieldIwouldmostliketobein”byscientistsinotherdisciplines.AstudentinphysicsmightreasonablyfeelthatallthegoodideashavealreadybeentakenbyGalileo,Newton,Einstein,andtherest,andthatittakesmanyyearsofstudybeforeonecancontributenewideas.AI,ontheotherhand,stillhasopeningsforafull-timeEinstein.

AIcurrentlyencompassesahugevarietyofsubfields,fromgeneral-purposeareassuchasperceptionandlogicalreasoning,tospecifictaskssuchasplayingchess,provingmathematicaltheorems,writingpoetry,anddiagnosingdiseases.Often,scientistsinotherfieldsmovegraduallyintoartificialintelligence,wheretheyfindthetoolsandvocabularytosystematizeandautomatetheintellectualtasksonwhichtheyhavebeenworkingalltheirlives.[2]Similarly,workersinAIcanchoosetoapplytheirmethodstoanyareaofhumanintellectualendeavor.Inthissense,itistrulyauniversalfield.1WhatisAI?

WehavenowexplainedwhyAIisexciting,butwehavenotsaidwhatitis.Definitionsofartificialintelligenceaccordingtoeightrecenttextbooksareshowninthetablebelow.Thesedefinitionsvaryalongtwomaindimensions.Theonesontopareconcernedwiththoughtprocessesandreasoning,whereastheonesonthebottomaddressbehavior.Also,thedefinitionsontheleftmeasuresuccessintermsofhumanperformance,whereastheonesontherightmeasureagainstanidealconceptofintelligence,whichwewillcallrationality.Asystemisrationalifitdoestherightthing.Table.1AIDefinitionVaryalongtwomaindimensions

Thisgivesusfourpossiblegoalstopursueinartificialintelligence:

Historically,allfourapproacheshavebeenfollowed.Asonemightexpect,atensionexistsbetweenapproachescenteredaroundhumansandapproachescenteredaroundrationality.Ahuman-centeredapproachmustbeanempiricalscience,involvinghypothesisandexperimentalconfirmation.Arationalistapproachinvolvesacombinationofmathematicsandengineering.Peopleineachgroupsometimescastaspersionsonworkdoneintheothergroups,butthetruthisthateachdirectionhasyieldedvaluableinsights.Letuslookateachinmoredetail.2ActingHumanly:theTuringTestApproach

TheTuringTest,proposedbyAlanTuring(Turing,1950),wasdesignedtoprovideasatisfactoryoperationaldefinitionofintelligence.Turingdefinedintelligentbehaviorastheabilitytoachievehuman-levelperformanceinallcognitivetasks,sufficienttofoolaninterrogator.Roughlyspeaking,thetestheproposedisthatthecomputershouldbeinterrogatedbyahumanviaateletype,andpassesthetestiftheinterrogatorcannottellifthereisacomputerorahumanattheotherend.Programmingacomputertopassthetestprovidesplentytoworkon.Thecomputerwouldneedtopossessthefollowingcapabilities:

naturallanguageprocessingtoenableittocommunicatesuccessfullyinEnglish(orsomeotherhumanlanguage);

knowledgerepresentationtostoreinformationprovidedbeforeorduringtheinterrogation;

automatedreasoningtousethestoredinformationtoanswerquestionsandtodrawnewconclusions;

machinelearningtoadapttonewcircumstancesandtodetectandextrapolatepatterns.

Turing’stestdeliberatelyavoideddirectphysicalinteractionbetweentheinterrogatorandthecomputer,becausephysicalsimulationofapersonisunnecessaryforintelligence.[3]However,theso-calledtotalTuringTestincludesavideosignalsothattheinterrogatorcantestthesubject’sperceptualabilities,aswellastheopportunityfortheinterrogatortopassphysicalobjects“throughthehatch.”TopassthetotalTuringTest,thecomputerwillneed

computervisiontoperceiveobjects,and

roboticstomovethemabout.

WithinAI,therehasnotbeenabigefforttotrytopasstheTuringtest.TheissueofactinglikeahumancomesupprimarilywhenAIprogramshavetointeractwithpeople,aswhenanexpertsystemexplainshowitcametoitsdiagnosis,oranaturallanguageprocessingsystemhasadialoguewithauser.Theseprogramsmustbehaveaccordingtocertainnormalconventionsofhumaninteractioninordertomakethemselvesunderstood.Theunderlyingrepresentationandreasoninginsuchasystemmayormaynotbebasedonahumanmodel.3ThinkingHumanly:theCognitiveModellingApproach

Ifwearegoingtosaythatagivenprogramthinkslikeahuman,wemusthavesomewayofdetermininghowhumansthink.Weneedtogetinsidetheactualworkingsofhumanminds.Therearetwowaystodothis:throughintrospection—tryingtocatchourownthoughtsastheygoby—orthroughpsychologicalexperiments.Oncewehaveasufficientlyprecisetheoryofthemind,itbecomespossibletoexpressthetheoryasacomputerprogram.Iftheprogram’sinput/outputandtimingbehaviormatcheshumanbehavior,thatisevidencethatsomeoftheprogram’smechanismsmayalsobeoperatinginhumans.Forexample,NewellandSimon,whodevelopedGPS,the“GeneralProblemSolver”(NewellandSimon,1961),werenotcontenttohavetheirprogramcorrectlysolveproblems.Theyweremoreconcernedwithcomparingthetraceofitsreasoningstepstotracesofhumansubjectssolvingthesameproblems.Thisisincontrasttootherresearchersofthesametime(suchasWang(1960)),whowereconcernedwithgettingtherightanswersregardlessofhowhumansmightdoit.TheinterdisciplinaryfieldofcognitivesciencebringstogethercomputermodelsfromAIandexperimentaltechniquesfrompsychologytotrytoconstructpreciseandtestabletheoriesoftheworkingsofthehumanmind.[4]4Thinkingrationally:Thelawsofthoughtapproach

TheGreekphilosopherAristotlewasoneofthefirsttoattempttocodify“rightthinking,”thatis,irrefutablereasoningprocesses.Hisfamoussyllogismsprovidedpatternsforargumentstructuresthatalwaysgavecorrectconclusionsgivencorrectpremises.Forexample,“Socratesisaman;allmenaremortal;thereforeSocratesismortal.”Theselawsofthoughtweresupposedtogoverntheoperationofthemind,andinitiatedthefieldoflogic.

Thedevelopmentofformallogicinthelatenineteenthandearlytwentiethcenturies,providedaprecisenotationforstatementsaboutallkindsofthingsintheworldandtherelationsbetweenthem.(Contrastthiswithordinaryarithmeticnotation,whichprovidesmainlyforequalityandinequalitystatementsaboutnumbers.)By1965,programsexistedthatcould,givenenoughtimeandmemory,takeadescriptionofaprobleminlogicalnotationandfindthesolutiontotheproblem,ifoneexists.(Ifthereisnosolution,theprogrammightneverstoplookingforit.)Theso-calledlogicisttraditionwithinartificialintelligencehopestobuildonsuchprogramstocreateintelligentsystems.

Therearetwomainobstaclestothisapproach.First,itisnoteasytotakeinformalknowledgeandstateitintheformaltermsrequiredbylogicalnotation,particularlywhentheknowledgeislessthan100%certain.Second,thereisabigdifferencebetweenbeingabletosolveaproblem“inprinciple”anddoingsoinpractice.Evenproblemswithjustafewdozenfactscanexhaustthecomputationalresourcesofanycomputerunlessithassomeguidanceastowhichreasoningstepstotryfirst.[5]Althoughbothoftheseobstaclesapplytoanyattempttobuildcomputationalreasoningsystems,theyappearedfirstinthelogicisttraditionbecausethepoweroftherepresentationandreasoningsystemsarewell-definedandfairlywellunderstood.5ActingRationally:theRationalAgentApproach

Actingrationallymeansactingsoastoachieveone’sgoals,givenone’sbeliefs.Anagentisjustsomethingthatperceivesandacts.(Thismaybeanunusualuseoftheword,butyouwillgetusedtoit.)Inthisapproach,AIisviewedasthestudyandconstructionofrationalagents.

Inthe“l(fā)awsofthought”approachtoAI,thewholeemphasiswasoncorrectinferences.Makingcorrectinferencesissometimespartofbeingarationalagent,becauseonewaytoactrationallyistoreasonlogicallytotheconclusionthatagivenactionwillachieveone’sgoals,andthentoactonthatconclusion.Ontheotherhand,correctinferenceisnotallofrationality,becausethereareoftensituationswherethereisnoprovablycorrectthingtodo,yetsomethingmuststillbedone.Therearealsowaysofactingrationallythatcannotbereasonablysaidtoinvolveinference.Forexample,pullingone’shandoffofahotstoveisareflexactionthatismoresuccessfulthanasloweractiontakenaftercarefuldeliberation.

Allthe“cognitiveskills”neededfortheTuringTestaretheretoallowrationalactions.Thus,weneedtheabilitytorepresentknowledgeandreasonwithitbecausethisenablesustoreachgooddecisionsinawidevarietyofsituations.Weneedtobeabletogeneratecomprehensiblesentencesinnaturallanguagebecausesayingthosesentenceshelpsusgetbyinacomplexsociety.Weneedlearningnotjustforerudition,butbecausehavingabetterideaofhowtheworldworksenablesustogeneratemoreeffectivestrategiesfordealingwithit.Weneedvisualperceptionnotjustbecauseseeingisfun,butinordertogetabetterideaofwhatanactionmightachieve—forexample,beingabletoseeatastymorselhelpsonetomovetowardit.

ThestudyofAIasrationalagentdesignthereforehastwoadvantages.First,itismoregeneralthanthe“l(fā)awsofthought”approach,becausecorrectinferenceisonlyausefulmechanismforachievingrationality,andnotanecessaryone.Second,itismoreamenabletoscientificdevelopmentthanapproachesbasedonhumanbehaviororhumanthought,becausethestandardofrationalityisclearlydefinedandcompletelygeneral.Humanbehavior,ontheotherhand,iswell-adaptedforonespecificenvironmentandistheproduct,inpart,ofacomplicatedandlargelyunknownevolutionaryprocessthatstillmaybefarfromachievingperfection.6TheStateoftheArt

InternationalgrandmasterArnoldDenkerstudiesthepiecesontheboardinfrontofhim.Herealizesthereisnohope;hemustresignthegame.Hisopponent,Hitech,becomesthefirstcomputerprogramtodefeatagrandmasterinagameofchess.

“IwanttogofromBostontoSanFrancisco,”thetravellersaysintothemicrophone.“Whatdatewillyoubetravellingon?”isthereply.ThetravellerexplainsshewantstogoOctober20th,nonstop,onthecheapestavailablefare,returningonSunday.AspeechunderstandingprogramnamedPegasushandlesthewholetransaction,whichresultsinaconfirmedreservationthatsavesthetraveller$894overtheregularcoachfare.Eventhoughthespeechrecognizergetsoneoutoftenwordswrong,itisabletorecoverfromtheseerrorsbecauseofitsunderstandingofhowdialogsareputtogether.

AnanalystintheMissionOperationsroomoftheJetPropulsionLaboratorysuddenlystartspayingattention.Aredmessagehasflashedontothescreenindicatingan“anomaly”withtheVoyagerspacecraft,whichissomewhereinthevicinityofNeptune.Fortunately,theanalystisabletocorrecttheproblemfromtheground.OperationspersonnelbelievetheproblemmighthavebeenoverlookedhaditnotbeenforMarvel,areal-timeexpertsystemthatmonitorsthemassivestreamofdatatransmittedbythespacecraft,handlingroutinetasksandalertingtheanalyststomoreseriousproblems.

CruisingthehighwayoutsideofPittsburghatacomfortable55mph,themaninthedriver’sseatseemsrelaxed.Heshouldbe—forthepast90miles,hehasnothadtotouchthesteeringwheel.Therealdriverisaroboticsystemthatgathersinputfromvideocameras,sonar,andlaserrangefindersattachedtothevan.Itcombinestheseinputswithexperiencelearnedfromtrainingrunsandsuccessfullycomputeshowtosteerthevehicle.

Aleadingexpertonlymph-nodepathologydescribesafiendishlydifficultcasetotheexpertsystem,andexaminesthesystem’sdiagnosis.Hescoffsatthesystem’sresponse.Onlyslightlyworried,thecreatorsofthesystemsuggestheaskthecomputerforanexplanationofthediagnosis.Themachinepointsoutthemajorfactorsinfluencingitsdecision,andexplainsthesubtleinteractionofseveralofthesymptomsinthiscase.Theexpertadmitshiserror,eventually.

Fromacameraperchedonastreetlightabovethecrossroads,thetrafficmonitorwatchesthescene.Ifanyhumanswereawaketoreadthemainscreen,theywouldsee“Citroen2CVturningfromPlacedelaConcordeintoChampsElysees,”“LargetruckofunknownmakestoppedonPlacedelaConcorde,”andsoonintothenight.Andoccasionally,“MajorincidentonPlacedelaConcorde,speedingvancollidedwithmotorcyclist,”andanautomaticcalltotheemergencyservices.

Thesearejustafewexamplesofartificialintelligencesystemsthatexisttoday.Notmagicorsciencefiction—butratherscience,engineering,andmathematics.1.?Homosapiensn.智人(現代人的學名)

2.?antigrarityn.反重力,反引力。

3.?endeavorn.努力,盡力vi.盡力,努力。

4.?dimensionn.尺寸,尺度,維(數),度(數),元。

5.?rationalityn.合理性,唯理性。

6.?hypothesisn.假設。Vocabulary

7.?aspersionn.灑水,誹謗,中傷。

8.?interrogatorn.訊問者,質問者。

9.?extrapolatev.推斷,[數]外推。

10.?cognitiveadj.認知的,認識的,有感知的。

11.?syllogismn.[邏]三段論法,推論法,演繹。

12.?mortaln.凡人,人類adj.必死的,致命的,人類的,臨終的。

13.?agentn.代理。

14.?inferencen.推論。

15.?stateoftheartn.技術發(fā)展水平。16.?Neptunen.[天]天王星。

17.?lymphn.淋巴腺,淋巴。

18.?pathologyn.病理學。

19.?fiendishlyadv.惡魔似地,極壞地。

20.?eruditionn.博學。

[1]Althoughnoonecanpredictthefutureindetail,itisclearthatcomputerswithhuman-levelintelligence(orbetter)wouldhaveahugeimpactonoureverydaylivesandonthefuturecourseofcivilization.

雖然沒有人可以詳細地預測未來,但是很顯然,具有人類智力水平(或更高水平)的電腦將會對我們的日常生活以及未來的文明進程產生巨大的影響。主句中it為形式主語,真正的主語是that引導的定語從句。ImportantSentences

[2]Often,scientistsinotherfieldsmovegraduallyintoartificialintelligence,wheretheyfindthetoolsandvocabularytosystematizeandautomatetheintellectualtasksonwhichtheyhavebeenworkingalltheirlives.

通常,其他領域的科學家逐步進入到了人工智能領域,他們在那里發(fā)現了能夠將他們一直所從事的工作系統化和自動化的工具和詞匯。where引導定語從句,修飾“artificialintelligence”。

[3]Turing’stestdeliberatelyavoideddirectphysicalinteractionbetweentheinterrogatorandthecomputer,becausephysicalsimulationofapersonisunnecessaryforintelligence.

圖靈測試刻意回避詢問者和計算機之間直接的物理交互,因為人的物理模擬對智能來說是不必要的。

[4]TheinterdisciplinaryfieldofcognitivesciencebringstogethercomputermodelsfromAIandexperimentaltechniquesfrompsychologytotrytoconstructpreciseandtestabletheoriesoftheworkingsofthehumanmind.

認知科學這個跨學科領域匯集了人工智能學的計算機模型以及心理學的實驗技巧,試圖構建人類頭腦運轉的準確的、可檢驗的理論。本句為一簡單句,結構為Theinterdisciplinaryfield…brings…to….。

[5]Evenproblemswithjustafewdozenfactscanexhaustthecomputationalresourcesofanycomputerunlessithassomeguidanceastowhichreasoningstepstotryfirst.

除非有應該首先執(zhí)行哪個推理步驟的提示,否則即使只有幾十個論據的問題也能耗盡任何一臺計算機的計算資源。

(1)?OnereasontostudyAIistolearnmoreaboutourselves,itisbecausethat().

A.?AIattemptstounderstandintelligententities

B.?AIattemptstobuildintelligententities

C.?AIisanintelligententities

D.?weareintelligententities

Multiple-choiceQuestions

(2)?Inthethirdparagraph,“AI,ontheotherhand,stillhasopeningsforafull-timeEinstein.”,whatisthemeaning?()

A.?InAI,there’remanynewideasforonetocontributeandmoreeasilytostudy.

B.?AIisnotoneofthenewestdisciplines.

C.?AllthegoodideashavealreadybeentakenbyGalileo,Newton,Einstein,andtherest.

D.?AIwasinitiatedformanyyears.

(3)?WhichistheTuringTest?

A.?Thecomputerandahumanshouldinterrogateeachother,andthec

溫馨提示

  • 1. 本站所有資源如無特殊說明,都需要本地電腦安裝OFFICE2007和PDF閱讀器。圖紙軟件為CAD,CAXA,PROE,UG,SolidWorks等.壓縮文件請下載最新的WinRAR軟件解壓。
  • 2. 本站的文檔不包含任何第三方提供的附件圖紙等,如果需要附件,請聯系上傳者。文件的所有權益歸上傳用戶所有。
  • 3. 本站RAR壓縮包中若帶圖紙,網頁內容里面會有圖紙預覽,若沒有圖紙預覽就沒有圖紙。
  • 4. 未經權益所有人同意不得將文件中的內容挪作商業(yè)或盈利用途。
  • 5. 人人文庫網僅提供信息存儲空間,僅對用戶上傳內容的表現方式做保護處理,對用戶上傳分享的文檔內容本身不做任何修改或編輯,并不能對任何下載內容負責。
  • 6. 下載文件中如有侵權或不適當內容,請與我們聯系,我們立即糾正。
  • 7. 本站不保證下載資源的準確性、安全性和完整性, 同時也不承擔用戶因使用這些下載資源對自己和他人造成任何形式的傷害或損失。

評論

0/150

提交評論