軟件Agent技術課程介紹鐘元生2008.2.251IntroductiontoTechnologyDefinitionsofSoftwareAgents24.1.20062IntroductiontoTechnologyIntroductionLittlebithistory.

Mid50’sfirstideasaboutsoftwareagents.JohnMcCarthy,OliverG.Selfridge.Researchonsoftwareagentscanbesplitintotwomainstrands:線繩firstoneaboutmid70’sandsecondoneatthebeginningof90’s.Todaysoftwareagentsarestillahot,diverse變化多的topic.distributedartificialintelligence,robotics,artificiallife,distributedobjectcomputing,human-computerinteraction,intelligentandadaptiveinterfaces,intelligentsearchandfiltering,informationretrieval檢索,etc.24.1.20063IntroductiontoTechnologyIntroductionAgents

Manydefinitions:

"Anagentisanythingthatcanbeviewedasperceivingitsenvironmentthroughsensorsandactinguponthatenvironmentthrougheffectors.”

"Autonomousagentsarecomputationalsystemsthatinhabitsomecomplexdynamicenvironment,senseandactautonomouslyinthisenvironment,andbydoingsorealizeasetofgoalsortasksforwhichtheyaredesigned."

"Intelligentagentsaresoftwareentitiesthatcarryoutsomesetofoperationsonbehalfofauseroranotherprogramwithsomedegreeofindependenceorautonomy,andinsodoing,employsomeknowledgeorrepresentationoftheuser'sgoalsordesires."24.1.20064IntroductiontoTechnologyIntroductionAgents

Manydefinitions:

“Letusdefineanagentasapersistent持久穩固的softwareentitydedicatedtoaspecificpurpose.‘Persistent’distinguishesagentsfromsubroutines子程序;agentshavetheirownideas主意abouthowtoaccomplishtasks,theirownagendas日程.‘Specialpurpose’distinguishesthemfromentiremultifunction多函數applications;agentsaretypicallymuchsmaller."

Anautonomousagentisasystemsituatedwithinandapartofanenvironmentthatsensesthatenvironmentandactsonit,overtime,inpursuitofitsownagendaand如此……以致于soastoeffectwhatitsensesinthefuture.24.1.20065IntroductiontoTechnologyIntroductionAutonomousAgentsBiologicalAgentsComputationalAgentsRoboticAgentsSoftwareAgentsArtificialLifeAgentsTask-specificAgentsEntertainmentAgentsVirusesCategoriesofagents(justoneofthem)機器人Agents生物Agents娛樂Agents特定任務的Agents24.1.20066IntroductiontoTechnologyIntroductionCategoriesofagents(justanotheroneofthem).

MobileagentsInterfaceagentsCollaborativeagentsInformationagentsReactive反應agentsHybrid混合agentsHeterogeneous異質agents24.1.20067IntroductiontoTechnologyIntroductiontoTechnologyWhatisanAgent?Attributes屬性AutonomyGoal-orientedMobileCollaborativeTemporalcontinuityAdaptivityCommunicativeProactive主動的自治移動主動的適應性溝通的協作的目標導向24.1.20068IntroductiontoTechnologyIntroductiontoTechnologyObjectsdoit,becauseAgentsdoitformoney...24.1.20069IntroductiontoTechnologyIntroductiontoTechnologyAgents'Architectures24.1.200610IntroductiontoTechnologyIntroductiontoTechnologyAgentArchitecturesMaes更多:Anarchitectureproposesaparticularmethodologyforbuildinganautonomousagent.Itspecifieshowtheoverallproblemcanbedecomposedintosubproblems,i.e.howtheconstructionoftheagentcanbedecomposedintotheconstructionofasetofcomponentmodulesandhowthesemodulesshouldbemadetointeract.Thetotalsetofmodulesandtheirinteractionshastoprovideananswertothequestionofhowthesensordataandthecurrentinternalstateoftheagentdeterminetheactions(effectoroutputs)andfutureinternalstateoftheagent.Anarchitectureencompassestechniquesandalgorithmsthatsupportthismethodology.24.1.200611IntroductiontoTechnologyIntroductiontoTechnologyAgentArchitectures

Reactive反應的agentDeliberative協商的？agentHybrid混合的agent24.1.200612IntroductiontoTechnologyIntroductiontoTechnologyReactiveAgentReactiveagentshaveatmostaverysimpleinternalrepresentationoftheworld,butprovidetightcoupling緊耦合ofperception感知andaction行為Behaviour-basedparadigm范例Intelligenceisaproductofinteractionbetweenanagentanditsenvironment.24.1.200613IntroductiontoTechnologyIntroductiontoTechnologyReactiveAgentEachbehaviourcontinuallymapsperceptualinputtoactionoutputReactivebehaviour: action:S->AwhereSdenotesthestatesoftheenvironment,andAtheprimitiveactionstheagentiscapableofperform.Example:action(s)= Heateroff,iftemperatureOKHeateron,otherwise24.1.200614IntroductiontoTechnologyIntroductiontoTechnologySensorsEffectorsAgentStimulus-responsebehavioursState1State2StatenAction1Action2Actionn......ReactiveAgent24.1.200615IntroductiontoTechnologyIntroductiontoTechnologyDeliberative協商？AgentExplicit清晰的symbolicmodeloftheworldinwhichdecisionsaremadevialogicalreasoning,basedonpatternmatchingandsymbolicmanipulationsense-plan-actproblem-solvingparadigmofclassicalAIplanningsystems24.1.200616IntroductiontoTechnologyIntroductiontoTechnologySensorsEffectorsWorldModelPlannerPlanexecutorAgentDeliberativeAgent24.1.200617IntroductiontoTechnologyIntroductiontoTechnologyAgents(intelligent).Internalarchitecture:Agentsmaintainaninternalrepresentationoftheirworld.Thereisanexplicitmental精神stateCanbemodifiedbysomeformofsymbolicreasoning.BDIagentsBeliefDesireIntentions24.1.200618IntroductiontoTechnologyIntroductiontoTechnologyAgent–aBDImodelEnvironmentperceptionworldmodelmentalmodelsocialmodelroutine/emergencysituationslocalplanningsituationsco-operatingsituationsreactionslocalgoalsco-operativegoalsoptionsintentionsPOBlocalplansjointplansACTIONbeliefssituationsgoalsselectionexecutiongoalactivationBeliefgenerationsituationrecognitionplanningandscheduling24.1.200619IntroductiontoTechnologyIntroductiontoTechnologyHybridAgentCombinationofdeliberativeandreactivebehaviourAnagentconsistsofseveralsubsystemsSubsystemsthatdevelopplansandmakedecisionsusing symbolicreasoning(deliberativecomponent)Reactivesubsystemsthatareabletoreactquicklytoeventswithoutcomplexreasoning(reactivecomponent)Layeredarchitectures24.1.200620IntroductiontoTechnologyIntroductiontoTechnologyAgentSensorsEffectorsReactivecomponentState1State2StatenAction2Actionn......WorldModelPlannerPlanexecutorDeliberativecomponentAction1observationsmodificationsHybridAgent24.1.200621IntroductiontoTechnologyIntroductiontoTechnologyEnvironmentofSoftwareAgents24.1.200622IntroductiontoTechnologyIntroductiontoTechnologyEnvironmentofSoftwareagents

AgentsPlatformsCommunicationsOntologyApplications24.1.200623IntroductiontoTechnologyIntroductiontoTechnologyPlatform24.1.200624IntroductiontoTechnologyIntroductiontoTechnologyPlatform

AplacewhereagentslivenotalwaysneededAgentmanagementcreation–terminationsecurityAgentcommunicationservicesAgentdirectoryservices24.1.200625IntroductiontoTechnologyIntroductiontoTechnologyExampleAgentPlatformAgentPlatformAgentManagementSystemDirectoryFacilitatorAgentCommunicationChannelAgentBaselineProtocolSoftwareAgentCommunicationChannelFIPA24.1.200626IntroductiontoTechnologyIntroductiontoTechnologyPlatforms-FIPAImplementations

Jade

(TiLab-TelecomItaly)LEAP (EU-project)BlueJade

(HP)FIPA-OS (Nortel-Emorphia)

MicroFIPA-OS (HY)24.1.200627IntroductiontoTechnologyIntroductiontoTechnologyQuestions?Comments.24.1.200628IntroductiontoTechnologyIntroductiontoTechnologyCommunications24.1.200629IntroductiontoTechnologyIntroductiontoTechnologyAgentCommunications

Modelledathigherabstractionlevelthan’traditional’datacommunications.

SpeechActtheoryJ.R.Searle(1969)SpeechActsClassicexample:Presidentsays”Ideclarewar”

isactuallyanaction.24.1.200630IntroductiontoTechnologyIntroductiontoTechnologySpeechacts

PragmatictheoryoflanguagedealingwiththesyntaxandsemanticsACLmessagetypesusuallymodeledafterspeechactsLocutionaryactutteringasyntacticallyacceptablesentenceIllocutionaryact(speechact)communicatingofthespeakers’intentionstothehearerPerlocutionaryactbringingaboutoftheeffectontheheareroftheutterance24.1.200631IntroductiontoTechnologyIntroductiontoTechnologyAgentCommunicationsKnowledgesharingAgentCommunicationLanguageInteractionProtocolsContentLanguage24.1.200632IntroductiontoTechnologyIntroductiontoTechnologyAgentCommunications24.1.200633IntroductiontoTechnologyIntroductiontoTechnologyAgentCommunicationLanguage(ACL)

KQML

(KnowledgeQueryandManipulationLanguage)

FIPA-ACL

(AgentCommunicationLanguage)24.1.200634IntroductiontoTechnologyIntroductiontoTechnologyAgentCommunicationLanguageFIPA-ACL24.1.200635IntroductiontoTechnologyIntroductiontoTechnologyCommunicativeactsAccept-proposalAgree Cancel Cfp Confirm Disconfirm Failure Inform

Inform-if(macroact)Inform-ref(macroact)Not-understood

Propagate Propose Proxy Query-if Query-ref Refuse Reject-proposalRequest

Request-when Request-wheneverSubscribe 24.1.200636IntroductiontoTechnologyIntroductiontoTechnologyThedoorisopen?Openthedoor(forme)OK!I’llopenthedoorThedoorisopen IamunabletoopenthedoorIwillnotopenthedoorSaywhenthedoorbecomesopenAnyonewanttoopenthedoor?Icanopenthedoorforyou..atapriceDoor?What’sthat?Don’tunderstand...queryrequestagreeinformfailurerefusesubscribecfpproposenot-understoodCommunicativeActs(cf.Dr.Poslad’sLecture)24.1.200637IntroductiontoTechnologyIntroductiontoTechnologyParameters

:sender:receiver:content:reply-with:reply-by:in-reply-to:envelope:language:ontology:protocol:conversation-id24.1.200638IntroductiontoTechnologyIntroductiontoTechnologyExampleofrequest

Thesenderrequeststhereceivertoperformsomeaction.(request

:senderi

:receiverj

:content"open\"db.txt\"forinput"

:languagevb)24.1.200639IntroductiontoTechnologyIntroductiontoTechnologySemanticofRequest

<i,request(j,a)>

FP:FP(a)[i\j]

BiAgent(j,a)

BiPGjDone(a)

RE:Done(a)i=sender,j=receiver,a=actiontoperformDone(a)=actionperformedBiAgent(j,a)=agentibelievesthatjcanperforma

BiPGjDone(a)=idoesnotbelievethatDone(a)isj

’spersistentgoal24.1.200640IntroductiontoTechnologyIntroductiontoTechnologyContentlanguages

FIPA-SLsubsetsSL0,SL1,andSL2FIPA-RDF0RDFbasedcontentlanguageFIPA-CCLConstraintChoiceLanguageKIF&FIPA-KIF24.1.200641IntroductiontoTechnologyIntroductiontoTechnologyContentlanguages

KIF(KnowledgeInterchangeFormat)

(salary015-46-3946widgets72000)(salary026-40-9152grommets36000)(salary415-32-4707fidgets42000)

(>(*(widthchip1)(lengthchip1))

(*(widthchip2)(lengthchip2)))24.1.200642IntroductiontoTechnologyIntroductiontoTechnologyContentlanguagesFIPA-SL

FormallanguageusedtodefinethesemanticsoftheFIPAACL

Logicalpropositionsareexpressedinalogicofmentalattitudesandactions,formalisedinafirstordermodallanguagewithidentity24.1.200643IntroductiontoTechnologyIntroductiontoTechnologyContentlanguageFIPA-SLexample(query-ref:sender(agent-identifier:nameB):receiver(set(agent-identifier:nameA)):content

(iota?x(UKPrimeMinister?x)):languageFIPA-SL:reply-withquery2)

(inform:sender(agent-identifier:nameA):receiver(set(agent-identifier:nameB)):content

(=(iota?x(UKPrimeMinister?x))"TonyBlair"):languageFIPA-SL:in-reply-toquery2)

24.1.200644IntroductiontoTechnologyIntroductiontoTechnologyInteractionprotocolsSpecifyagentcommunicationpatterns.Example:24.1.200645IntroductiontoTechnologyIntroductiontoTechnologyFIPAinteractionprotocolsRequestQueryRequestWhenContractNetIteratedContractNetEnglishAuctionDutchAuctionBrokeringSubscribeBrokeringPropose24.1.200646IntroductiontoTechnologyIntroductiontoTechnologyQuestions?Comments.24.1.200647IntroductiontoTechnologyIntroductiontoTechnologyOntology24.1.200648IntroductiontoTechnologyIntroductiontoTechnologyOntology

Howdocommunicatingagentsunderstandeachother?

Systemswhichcommunicateandworktogethermustshareanontology.

Ontology

Acommonvocabularyandagreeduponmeaningstodescribeasubjectdomain.Anontologyisaspecificationofaconceptualization.Anontologyisadescriptionoftheconceptsandrelationshipsthatcanexistforanagentoracommunityofagents.24.1.200649IntroductiontoTechnologyIntroductiontoTechnologyOntology

Thesharedontologycanbeimplicitorexplicit.Implicitontologyaretypicallyrepresentedonlybyprocedures.Explicitontologyare(ideally)givenadeclarativerepresentationinawelldefinedknowledgerepresentationlanguage.24.1.200650IntroductiontoTechnologyIntroductiontoTechnologyOntologyExample24.1.200651IntroductiontoTechnologyIntroductiontoTechnologyOWL(WebOntologyLanguage)byW3COWLisdesignedforusebyapplicationsthatneedtoprocessthecontentofinformationinsteadofjustpresentinginformationtohumans.OWLisanextensiontoRDFandRDFSchemaThreesublanguages:OWLLiteclassificationhierarchyandsimpleconstraintsOWLDLmaximumexpressiveness,computationalcompleteness,anddecidabilityOWLFullmaximumexpressivenessandthesyntacticfreedomofRDFwithnocomputationalguarantees.24.1.200652IntroductiontoTechnologyIntroductiontoTechnologyOWLOWLextendsvocabularydescriptionallowingtoexpressclaimssuchas...Nothingcanbebothwineandbeer.grandParentandgrandChildareinverses.homepageisuniquelyidentifyingproperty.AW3CTeamPersonisaPersonwhoseworkplaceHomepageis/24.1.200653IntroductiontoTechnologyIntroductiontoTechnologyOWLOWLaddsvaluetotheSemanticWeballowingmachine-checkableontologydesignallowinginferringnewknowledgeallowingautomaticdetectionofcontradictionsprovidingprinciplesforcomplexdatamerging24.1.200654IntroductiontoTechnologyIntroductiontoTechnologyEnvironmentsofAgent24.1.200655IntroductiontoTechnologyIntroductiontoTechnologyEnvironmentsofsoftwareagents-anotherviewpoint

Accessiblevsinaccessible

Anaccessibleenvironmentisoneinwhichtheagentcanobtaincomplete,accurate,up-to-dateinformationabouttheenvironment’sstate.Mostmoderatelycomplexenvironments(including,forexample,theeverydayphysicalworldandtheInternet)areinaccessible.Themoreaccessibleanenvironmentis,thesimpleritistobuildagentstooperateinit.24.1.200656IntroductiontoTechnologyIntroductiontoTechnologyEnvironmentsofsoftwareagents

Deterministicvsnon-deterministic

Adeterministicenvironmentisoneinwhichanyactionhasasingleguaranteedeffect—thereisnouncertaintyaboutthestatethatwillresultfromperforminganaction.Thephysicalworldcantoallintentsandpurposesberegardedasnon-deterministic.Non-deterministicenvironmentspresentgreaterproblemsfortheagentdesigner.24.1.200657IntroductiontoTechnologyIntroductiontoTechnologyEnvironmentsofsoftwareagents

Episodicvsnon-episodic

Inanepisodicenvironment,theperformanceofanagentisdependentonanumberofdiscreteepisodes,withnol