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1、Two-SidedMatchingwithPartialInformationBAHARAKRASTEGARI,UniversityofBritishColumbiaANNECONDON,UniversityofBritishColumbiaNICOLEIMMORLICA,NorthwesternUniversityKEVINLEYTON-BROWN,UniversityofBritishColumbiaThetraditionalmodeloftwo-sidedmatchingassumesthatall
2、agentsfullyknowtheirownpreferences.Asmarketsgrowlarge,however,itbecomesimpracticalforagentstopreciselyassesstheirrankingsoverallagentsontheothersideofthemarket.Weproposeanovelmodeloftwo-sidedmatchinginwhichagentsareendowedwithknownpartiallyorderedpreferenc
3、esandunknowntruepreferencesdrawnfromknowndistributionsconsistentwiththepartialorder.Thetruepreferencesarelearnedthroughinterviews,revealingthepairwiserankingsamongallinterviewedagents,performedaccordingtoacentralizedinterviewpolicy,i.e.,analgorithmthatadap
4、tivelyschedulesinterviews.Ourgoalisforthepolicytoguaranteebothstabilityandoptimalityforagivensideofthemarket,withrespecttotheunderlyingtruepreferencesoftheagents.Asinterviewsarecostly,weseekapolicythatminimizesthenumberofinterviews.Weintroducethreeminimiza
5、tionobjectives:(veryweak)dominance,whichminimizesthenumberofinterviewsforanyunderlyingtruepreferenceprole;Paretooptimality,whichguaranteesthatnootherpolicydominatesthegivenpolicy;andoptimalityinexpectationwithrespecttothepreferencedistribution.Weformulate
6、ourproblemasaMarkovdecisionprocess,implyinganalgorithmforcomputinganoptimal-in-expectationpolicyintimepolynomialinthenumberofpossiblepreferenceorderings(andthusexponentialinthesizeoftheinput).Wethenderivestructuralpropertiesofdominantpolicieswhichwecallopt
7、imalitycerticates.WeshowthatcomputingaminimumoptimalitycerticateisNP-hard,suggestingthatoptimal-in-expectationand/orParetooptimalpoliciescouldbeNP-hardtocompute.Finally,werestrictattentiontoasettinginwhichagentsononesideofthemarkethavethesamepartiallyord
8、eredpreferences(butpotentiallydistinctunderlyingtruepreferences),andinwhichagentsmustinterviewbeforematching.Inthisrestrictedsetting,weshowhowtoleveragetheideaofminimumoptimalitycerticatestodesignacomputatio