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软件Agent技术课程介绍钟元生2008.2.251IntroductiontoTechnologyDefinitionsofSoftwareAgents24.1.20062IntroductiontoTechnologyIntroductionLittlebithistory.
Mid50’sfirstideasaboutsoftwareagents.JohnMcCarthy,OliverG.Selfridge.Researchonsoftwareagentscanbesplitintotwomainstrands:线绳firstoneaboutmid70’sandsecondoneatthebeginningof90’s.Todaysoftwareagentsarestillahot,diverse变化多的topic.distributedartificialintelligence,robotics,artificiallife,distributedobjectcomputing,human-computerinteraction,intelligentandadaptiveinterfaces,intelligentsearchandfiltering,informationretrieval检索,etc.24.1.20063IntroductiontoTechnologyIntroductionAgents
Manydefinitions:
"Anagentisanythingthatcanbeviewedasperceivingitsenvironmentthroughsensorsandactinguponthatenvironmentthrougheffectors.”
"Autonomousagentsarecomputationalsystemsthatinhabitsomecomplexdynamicenvironment,senseandactautonomouslyinthisenvironment,andbydoingsorealizeasetofgoalsortasksforwhichtheyaredesigned."
"Intelligentagentsaresoftwareentitiesthatcarryoutsomesetofoperationsonbehalfofauseroranotherprogramwithsomedegreeofindependenceorautonomy,andinsodoing,employsomeknowledgeorrepresentationoftheuser'sgoalsordesires."24.1.20064IntroductiontoTechnologyIntroductionAgents
Manydefinitions:
“Letusdefineanagentasapersistent持久稳固的softwareentitydedicatedtoaspecificpurpose.‘Persistent’distinguishesagentsfromsubroutines子程序;agentshavetheirownideas主意abouthowtoaccomplishtasks,theirownagendas日程.‘Specialpurpose’distinguishesthemfromentiremultifunction多函数applications;agentsaretypicallymuchsmaller."
Anautonomousagentisasystemsituatedwithinandapartofanenvironmentthatsensesthatenvironmentandactsonit,overtime,inpursuitofitsownagendaand如此……以致于soastoeffectwhatitsensesinthefuture.24.1.20065IntroductiontoTechnologyIntroductionAutonomousAgentsBiologicalAgentsComputationalAgentsRoboticAgentsSoftwareAgentsArtificialLifeAgentsTask-specificAgentsEntertainmentAgentsVirusesCategoriesofagents(justoneofthem)机器人Agents生物Agents娱乐Agents特定任务的Agents24.1.20066IntroductiontoTechnologyIntroductionCategoriesofagents(justanotheroneofthem).
MobileagentsInterfaceagentsCollaborativeagentsInformationagentsReactive反应agentsHybrid混合agentsHeterogeneous异质agents24.1.20067IntroductiontoTechnologyIntroductiontoTechnologyWhatisanAgent?Attributes属性AutonomyGoal-orientedMobileCollaborativeTemporalcontinuityAdaptivityCommunicativeProactive主动的自治移动主动的适应性沟通的协作的目标导向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反应的agentDeliberative协商的?agentHybrid混合的agent24.1.200612IntroductiontoTechnologyIntroductiontoTechnologyReactiveAgentReactiveagentshaveatmostaverysimpleinternalrepresentationoftheworld,butprovidetightcoupling紧耦合ofperception感知andaction行为Behaviour-basedparadigm范例Intelligenceisaproductofinteractionbetweenanagentanditsenvironment.24.1.200613IntroductiontoTechnologyIntroductiontoTechnologyReactiveAgentEachbehaviourcontinuallymapsperceptualinputtoactionoutputReactivebehaviour: action:S->AwhereSdenotesthestatesoftheenvironment,andAtheprimitiveactionstheagentiscapableofperform.Example:action(s)= Heateroff,iftemperatureOKHeateron,otherwise24.1.200614IntroductiontoTechnologyIntroductiontoTechnologySensorsEffectorsAgentStimulus-responsebehavioursState1State2StatenAction1Action2Actionn......ReactiveAgent24.1.200615IntroductiontoTechnologyIntroductiontoTechnologyDeliberative协商?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
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