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1、BeerGameComputersPlay:CanArtificialAgentsManageSupplyChain?CorrespondingauthorisD.J.Wu,hiscurrentaddressis:101North33rdStreet,AcademicBuilding,Philadelphia,PA19104.Email:wudj@drexel.edu.StevenO.Kimbrough,D.-J.Wu,FangZhongDepartmentofOperationsandInformationManagementTheWhartonSchoolUnive
2、rsityofPennsylvaniaandDepartmentofManagementBennettS.LeBowCollegeofBusinessDrexelUniversityPhiladelphia,PA19104U.S.A.May,2000AbstractInthisstudy,webuildanelectronicsupplychainthatismanagedbyartificialagents.WeinvestigateifartificialagentsdobetterthanhumanbeingswhenplayingtheMIT“BeerGame”
3、bymitigatingtheBullwhipeffectorbydiscoveringgoodandeffectivebusinessstrategies.Inparticular,westudythefollowingquestions:Canagentslearnreasonablygoodpoliciesinthefaceofdeterministicdemandwithfixedlead-time?Canagentstrackreasonablywellinthefaceofstochasticdemandwithstochasticlead-time?Can
4、agentslearnandadaptinvariouscontentstoplaythegame?Canagentscooperateacrossthesupplychain?Whatkindofmechanismsinducescoordination,cooperationandinformationsharingamongagentsintheelectronicsupplychainwhenfacingautomatedelectronicmarkets?KEYWORDSANDPHRASES:ArtificialAgents,BeerGame,SupplyCh
5、ainManagement,BusinessStrategies.1.IntroductionWeproposeaframeworkthattreatsanautomatedenterpriseasanelectronicsupplychainthatconsistsofvariousartificialagents.Inparticular,weviewsuchavirtualenterpriseasaMAS.AclassicalexampleofsupplychainmanagementistheMITBeerGame,whichhasattractedgreata
6、ttentionfromboththesupplychainmanagementpractitionersaswellasacademicresearchers.Thereareseveraltypesofagentsinthischain,forexample,theretailer,distributor,wholesaler,andmanufacturer.Eachself-interestedagenttriestoachieveitsowngoalsuchasminimizeitsinventorycostbymakingorderstoitssupplier
7、.Eachagentmakesitsownpredictiononfuturedemandofitscustomerbasedonitsobservation.Duetolackoftheincentivesofinformationsharingandboundedrationalityofeachagent,theobservedorexperimentperformanceofrealagents(humanbeings)managingsuchasupplychainisusuallyfarfromoptimalfromasyst
