Grossi & Pigozzi PDF
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F FFooorr r m mmooorreree i ininnffofoorrmrmmaaattitioioonnn RRR GGG vvviisisisitit t w wwwwwwww..m.mmooorrrgggaaannncccllalaayyypppooooooll.l.c.ccooommm AAA NNN &&& SSSyyynnnttthhheeeSSSiiiSSS LLLeeeccctttuuurrreeeSSS ooonnn AAArrrtttiiifffiiiccciiiAAALLL IIISSSBBBNNN::: 999777888---111---666222777000555---000888777---666 CCC MMMOOORRRGGGAAANNN&&&CCCLLLAAAYYYPPPOOOOOOLLL PPPUUUBBBLLLIIISSSHHHEEERRRSSS 999000000000000 LLL AAA iiinnnttteeeLLLLLLiiigggeeennnccceee AAAnnnddd MMMAAAccchhhiiinnneee LLLeeeAAArrrnnniiinnnggg YYY PPP wwwwwwwww...mmmooorrrgggaaannnccclllaaayyypppoooooolll...cccooommm OOO 999777888111666222777000555000888777666 OOO LLL RRRooonnnaaalldldd J JJ.. . B BBrrraaaccchhhmmmaaannn,, , W WWiililllliliaiaammm W WW.. . C CCooohhheeennn,, , a aannnddd P PPeeettteeerrr S SStttooonnneee,, , S SSeeerrriiieeesss E EEdddiiitttooorrrsss Judgment Aggregation: A Primer Synthesis Lectures on Artificial Intelligence and Machine Learning Editors RonaldJ.Brachman,Yahoo!Labs WilliamW.Cohen,CarnegieMellonUniversity PeterStone,UniversityofTexasatAustin JudgmentAggregation:APrimer DavideGrossiandGabriellaPigozzi 2014 AnIntroductiontoConstraint-BasedTemporalReasoning RomanBártak,RobertA.Morris,andK.BrentVenable 2014 ReasoningwithProbabilisticandDeterministicGraphicalModels:ExactAlgorithms RinaDechter 2013 IntroductiontoIntelligentSystemsinTrafficandTransportation AnaL.C.BazzanandFranziskaKlügl 2013 AConciseIntroductiontoModelsandMethodsforAutomatedPlanning HectorGeffnerandBlaiBonet 2013 EssentialPrinciplesforAutonomousRobotics HenryHexmoor 2013 Case-BasedReasoning:AConciseIntroduction BeatrizLópez 2013 iv AnswerSetSolvinginPractice MartinGebser,RolandKaminski,BenjaminKaufmann,andTorstenSchaub 2012 PlanningwithMarkovDecisionProcesses:AnAIPerspective MausamandAndreyKolobov 2012 ActiveLearning BurrSettles 2012 ComputationalAspectsofCooperativeGameeory GeorgiosChalkiadakis,EdithElkind,andMichaelWooldridge 2011 RepresentationsandTechniquesfor3DObjectRecognitionandSceneInterpretation DerekHoiemandSilvioSavarese 2011 AShortIntroductiontoPreferences:BetweenArtificialIntelligenceandSocialChoice FrancescaRossi,KristenBrentVenable,andTobyWalsh 2011 HumanComputation EdithLawandLuisvonAhn 2011 TradingAgents MichaelP.Wellman 2011 VisualObjectRecognition KristenGraumanandBastianLeibe 2011 LearningwithSupportVectorMachines ColinCampbellandYimingYing 2011 AlgorithmsforReinforcementLearning CsabaSzepesvári 2010 DataIntegration:eRelationalLogicApproach MichaelGenesereth 2010 v MarkovLogic:AnInterfaceLayerforArtificialIntelligence PedroDomingosandDanielLowd 2009 IntroductiontoSemi-SupervisedLearning XiaojinZhuandAndrewB.Goldberg 2009 ActionProgrammingLanguages Michaelielscher 2008 RepresentationDiscoveryusingHarmonicAnalysis SridharMahadevan 2008 EssentialsofGameeory:AConciseMultidisciplinaryIntroduction KevinLeyton-BrownandYoavShoham 2008 AConciseIntroductiontoMultiagentSystemsandDistributedArtificialIntelligence NikosVlassis 2007 IntelligentAutonomousRobotics:ARobotSoccerCaseStudy PeterStone 2007 Copyright©2014byMorgan&Claypool Allrightsreserved.Nopartofthispublicationmaybereproduced,storedinaretrievalsystem,ortransmittedin anyformorbyanymeans—electronic,mechanical,photocopy,recording,oranyotherexceptforbriefquotations inprintedreviews,withoutthepriorpermissionofthepublisher. JudgmentAggregation:APrimer DavideGrossiandGabriellaPigozzi www.morganclaypool.com ISBN:9781627050876 paperback ISBN:9781627050883 ebook DOI10.2200/S00559ED1V01Y201312AIM027 APublicationintheMorgan&ClaypoolPublishersseries SYNTHESISLECTURESONARTIFICIALINTELLIGENCEANDMACHINELEARNING Lecture#27 SeriesEditors:RonaldJ.Brachman,Yahoo!Labs WilliamW.Cohen,CarnegieMellonUniversity PeterStone,UniversityofTexasatAustin SeriesISSN SynthesisLecturesonArtificialIntelligenceandMachineLearning Print1939-4608 Electronic1939-4616 Judgment Aggregation: A Primer Davide Grossi UniversityofLiverpool Gabriella Pigozzi UniversitéParisDauphine SYNTHESISLECTURESONARTIFICIALINTELLIGENCEANDMACHINE LEARNING#27 M &C Morgan &cLaypool publishers ABSTRACT Judgment aggregation is a mathematical theory of collective decision-making. It concerns the methods whereby individual opinions about logically interconnected issues of interest can, or cannot, be aggregated into one collective stance. Aggregation problems have traditionally been of interest for disciplines like economics and the political sciences, as well as philosophy, where judgmentaggregationitselforiginatesfrom,buthaverecentlycapturedtheattentionofdisciplines likecomputerscience,artificialintelligenceandmulti-agentsystems.Judgmentaggregationhas emerged in the last decade as a unifying paradigm for the formalization and understanding of aggregationproblems.Still,nocomprehensivepresentationofthetheoryisavailabletodate.is SynthesisLectureaimsatfillingthisgappresentingthekeymotivations,results,abstractionsand techniquesunderpinningit. KEYWORDS judgmentaggregation,collectivedecision-making,logic,socialchoicetheory,com- putationalsocialchoice,preferenceaggregation,votingparadoxes,aggregationrules, impossibilityresults,manipulability,ultrafilters,opinionpooling,deliberation
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