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一种基于CAS的代理主体行为仿真模型
Title:AgentBehaviorSimulationModelbasedonCAS:AReview
Abstract:
Thecomplexityofreal-worldsystemsrequiresthedevelopmentofsimulationmodelsthatcanaccuratelysimulatethebehaviorsofvariousentitiesinvolved.Inthispaper,wefocusonthesimulationofagentbehaviorusingtheComplexAdaptiveSystems(CAS)approach.WereviewexistingliteratureonagentbehaviorsimulationmodelsbasedonCASprinciples,discusstheirkeycomponents,andprovideinsightsintotheirapplicationsandlimitations.Bypresentingacomprehensiveoverview,thispaperaimstocontributetotheunderstandingandadvancementofagentbehaviorsimulationmodelsbasedonCAS.
1.Introduction:
ComplexAdaptiveSystems(CAS)isatheoreticalframeworkthatstudiesthebehaviorsandinteractionsofindividualagentswithinalargersystem.CASemphasizestheemergenceofcollectivebehaviorsandpatternsthroughtheinteractionandadaptationofagents.Agent-basedmodeling,rootedinCAS,allowsforthesimulationofagentbehaviorinvarioussocial,biological,andphysicalsystems.
2.ComponentsofAgentBehaviorSimulationModelsbasedonCAS:
2.1Agents:
Agentsareautonomousentitiesthatpossessbehaviors,preferences,knowledge,anddecision-makingcapabilities.Theyinteractwithotheragentsandtheenvironment,adaptingtheirbehaviorsbasedonfeedbackandthebroadersystemdynamics.
2.2Environments:
Environmentsprovidethecontextforagentinteractions.Theycanbephysicalspaces,socialnetworks,virtualworlds,oranyothersysteminwhichagentsoperate.Environmentsinfluenceagentbehaviorsandprovidefeedbackthataffectsagentdecision-making.
2.3Interactions:
Interactionsoccurbetweenagentsandwiththeirenvironment.Theyinvolveinformationexchange,resourceallocation,collaboration,competition,andotherformsofcooperationthatshapeagentbehaviorsandsystemdynamics.
2.4Communication:
Communicationplaysavitalroleinagentinteractions.Agentsexchangeinformation,influenceeachother'sdecisions,andcoordinatetheiractions.Communicationmechanisms,suchasdirectcommunication,indirectsignaling,ormediatedmessages,impacttheemergenceofcollectivebehaviors.
2.5LearningandAdaptation:
A