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Cognitive hierarchies and emotions in behavioral game theory Colin F. Camerer 1, 2 Alec Smith 1 1 Division of Humanities and Social Sciences 2 Computation and Neural Systems California Institute of Technology 4/25/11 11:15 am. Comments welcome. Prepared for Oxford Handbook of Thinking and Reasoning (K. J. Holyoak & R. G. Morrison, Editors). This research was supported by The Betty and Gordon Moore Foundation and by National Science Foundation grant NSF‐SES 0850840. Correspondence to: [email protected].
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Page 1: Cognitive hierarchies and emotions in behavioral game …ajyu/Teaching/Cogs200_fa11/Readings/camerer... · Cognitive hierarchies and emotions in behavioral game theory Colin F. Camerer1,

Cognitivehierarchiesandemotions

inbehavioralgametheory

ColinF.Camerer1,2

AlecSmith1

1DivisionofHumanitiesandSocialSciences

2ComputationandNeuralSystems

CaliforniaInstituteofTechnology

4/25/1111:15am.Commentswelcome.PreparedforOxfordHandbookofThinkingand

Reasoning(K.J.Holyoak&R.G.Morrison,Editors).ThisresearchwassupportedbyThe

BettyandGordonMooreFoundationandbyNationalScienceFoundationgrantNSF‐SES

0850840.Correspondenceto:[email protected].

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ABSTRACT

Untilrecently,gametheorywasnotfocussedoncognitively‐plausiblemodelsofchoicesin

humanstrategicinteractions.Thischapterdescribestwonewapproachesthatdoso.The

firstapproach,cognitivehierarchymodeling,assumesthatplayershavedifferentlevelsof

partiallyaccuraterepresentationsofwhatothersarelikelytodo,whichvaryfromheuristic

andnaïvetohighlysophisticatedandaccurate.Thereisreasonableevidencethatthis

approachexplainschoices(betterthantraditionalequilibriumanalysis)indozensof

experimentalgamesandsomenaturally‐occurringgames(e.g.,aSwedishlottery,auctions,

andconsumerreactionstoundisclosedqualityinformationaboutmovies).Measurementof

eyetrackingandfMRIactivityduringgamesisalsosuggestiveofacognitive.Thesecond

approach,psychologicalgames,allowsvaluetodependuponchoiceconsequencesandon

beliefsaboutwhatwillhappen.Thismodelingframeworkcanlinkcognitionandemotion,

andexpresssocialemotionssuchas“guilt”.Inapsychologicalgame,guiltismodeledasthe

negativeemotionofknowingthatanotherpersonisunpleasantlysurprisedthatyour

choicedidnotbenefitthem(astheyhadexpected).Ourhopeisthatthesenew

developmentsinatraditionallycognitivefield(gametheory)willengageinterestof

psychologistsandothersinterestedinthinkingandsocialcognition.

KEYWORDS

Boundedrationality,cognitivehierarchy,emotions,gametheory,psychologicalgames,

strategicneuroscience

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I.Introduction

Thischapterisaboutcognitiveprocessesinstrategicthinking.Thetheoryofgames

providesthemostcomprehensiveframeworkforthinkingaboutthevaluedoutcomesthat

resultfromstrategicinteractions.Thetheoryspecifieshow“players”(that’sgametheory

jargon)mightchoosehigh‐valuestrategiestoguesslikelychoicesofotherplayers.

Traditionally,gametheoryhasbeenfocusedonfinding“solutions”togamesbasedon

highlymathematicalconceptionsofrationalforecastingandchoice.Morerecently(starting

withCamerer,1990),behavioralgametheorymodelshaveextendedtherationaltheories

toincludestochasticresponse,limitsoninferringcorrectlywhatotherplayerswilldo,

socialemotionsandconsiderationssuchasguilt,anger,reciprocity,orsocialimage,and

modulatingfactorsincludinginferencesaboutothers’intentions.Twogeneralbehavioral

modelsthatmightinterestcognitivepsychologistsarethefocusofthischapteri:Cognitive

hierarchymodeling,andpsychologicalgametheory.

Conventionalgametheoryistypicallyabstract,mathematicallyintimidating,

computationallyimplausible,andalgorithmicallyincomplete.Itisthereforenotsurprising

thatconventionaltoolshavenotgainedtractionincognitivepsychology.Ourhopeisthat

themorepsychologicallyplausiblebehavioralvariantscouldinterestcognitive

psychologists.Oncelimitedstrategicthinkingisthefocus,questionsofcognitive

representation,categorizationofdifferentstrategicstructures,andthenatureofsocial

cognition,andhowcooperationisachievedallbecomemoreinterestingresearchable

questions.Thequestionofwhetherornotpeopleareusingthedecision‐makingalgorithms

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proposedbythesebehavioralmodelscanalsobeaddressedwithobservables(suchas

responsetimesandeyetrackingofvisualattention)familiarincognitivepsychology.

Numericalmeasuresofvalueandbeliefderivedinthesetheoriescanalsobeusedas

parametricregressorstoidentifycandidatebraincircuitsthatappeartoencodethose

measures.Thisgeneralapproachhasbeenquitesuccessfulinstudyingsimpler

nonstrategicchoicedecisions(Glimcher,Camerer,Fehr,&Poldrack,2008)buthasbeen

appliedinfrequentlytogames(seeBhatt&Camerer,inpress).

Whatisagame?

Gametheoryisthemathematicalanalysisofstrategicinteraction.Ithasbecomea

standardtoolineconomicsandtheoreticalbiology,andisincreasinglyusedinpolitical

science,sociology,andcomputerscience.Agameismathematicallydefinedasasetof

players,descriptionsoftheirinformation,afixedorderofthesequenceofchoicesby

differentplayers,andafunctionmappingplayers’choicesandinformationtooutcomes.

Outcomesmayincludetangibleslikecorporateprofitsorpokerwinnings,aswellas

intangibleslikepoliticalgain,status,orreproductiveopportunities(inbiologicaland

evolutionarypsychologymodels).Thespecificationofagameiscompletedbyapayoff

functionthatattachesanumericalvalueor“utility”toeachoutcome.

Thestandardapproachtotheanalysisofgamesistocomputeanequilibriumpoint,

asetofstrategiesforeachplayerwhicharesimultaneouslybestresponsestooneanother..

ThisapproachisdueoriginallytoJohnNash(1950),buildingonearlierworkbyVon

NeumannandMorgenstern(1947).Solvingforequilibriummathematicallyrequires

solvingsimultaneousequationsinwhicheachplayer'sstrategyisaninputtotheother

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player'scalculationofexpectedpayoff.Thesolutionisacollectionofstrategies,onefor

eachplayer,whereeachplayer’sstrategymaximizeshisexpectedpayoffgiventhe

strategiesoftheotherplayers.

Fromthebeginningofgametheory,howequilibriummightarisehasbeenthe

subjectofongoingdiscussion.Nashhimselfsuggestedthatequilibriumbeliefsmight

resolvefromchangesin“massaction”aspopulationslearnaboutwhatothersdoand

adjusttheirstrategiestowardoptimization.ii

MorerecentlygametheoristshaveconsideredtheepistemicrequirementsforNash

equilibriumbytreatinggamesasinteractivedecisionproblems(cf.Brandenburger1992).

ItturnsoutthatNashequilibriumforn‐playergamesrequiresverystrongassumptions

abouttheplayers’mutualknowledge:thatallplayersshareacommonpriorbeliefabout

chanceevents,knowthatallplayersarerational,andknowthattheirbeliefsarecommon

knowledge(Aumann&Brandenburger1995).iiiThelatterrequirementimpliesthat

rationalplayersbeabletocomputebeliefsaboutthestrategiesofcoplayersandallstates

oftheworld,beliefsaboutbeliefs,andsoon,adinfinitum.

TwoBehavioralApproaches:CognitiveHierarchyandPsychologicalGames

Cognitivehierarchy(CH)andpsychologicalgames(PG)modelsbothmodify

assumptionsfromgametheorytocapturebehaviormorerealistically.

TheCHapproachassumesthatboundedlyrationalplayersarelimitedinthe

numberofinterpersonaliterationsofstrategicreasoningtheycan(orchoose)todo.There

arefiveelementstoanyCHpredictivemodel:

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1. Adistributionofthefrequencyofleveltypesf(k)

2. Actionsoflevel0players;

3. Beliefsoflevel‐kplayers(fork=1,2,…)aboutotherplayers;

4. Assessingexpectedpayoffsbasedonbeliefsin(3).

5. Astochasticchoiceresponsefunctionbasedontheexpectedpayoffsin(4)

Thetypicalapproachistomakepreciseassumptionsaboutelements(1‐5)andsee

howwellthatspecificmodelfitsexperimentaldatafromdifferentgames.Justasintesting

acookingrecipe,ifthemodelfailsbadlythenitcanbeextendedandimproved.

InCamerer,HoandChong(2004),thedistributionoflevelktypesisassumedto

followaPoissondistributionwithameanvalueτ.Oncethevalueofτischosen,the

completedistributionisknown.ThePoissondistributionhasthesensiblepropertythatthe

frequenciesofveryhighleveltypeskdropsoffquicklyforhighervaluesofk.(Forexample,

iftheaveragenumberofthinkingstepsτ=1.5,thenlessthan2%ofplayersareexpectedto

dofiveormorestepsofthinking.)

Tofurtherspecifythemodel,level0typesareusuallyassumedtochooseeach

strategyequallyoften.ivIntheCHapproach,levelkplayersknowthecorrectproportions

oflower‐levelplayers,butdonotrealizethereareotherevenhigher‐levelplayers(perhaps

reflectingoverconfidenceinrelativeability).Analternativeassumption(called“levelk”

modeling)isthatalevelkplayerthinksallotherplayersareatlevelk‐1.

Undertheseassumptions,eachlevelofplayerinahierarchycanthencomputethe

expectedpayoffstodifferentstrategies:Level1’scomputetheirexpectedpayoff(knowing

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whatlevel0’swilldo);level2’scomputetheexpectedpayoffgiventheirguessaboutwhat

level1’sand0’sdo,andhowfrequentthoseleveltypesare;andsoforth.Inthesimplest

formofthemodel,playerschoosethestrategywiththehighestexpectedpayoff(the“best

response”);butitisalsoeasytousealogisticorpowerstochastic“betterresponse”

function(e.g.,Luce,1959).Becausethetheoryishierarchical,itiseasytoprogramand

solvenumericallyusinga“loop”.

Psychologicalgamesmodelsassumethatplayersarerationalinthesensethatthey

maximizetheirexpectedutilitygivenbeliefsandtheutilityfunctionsoftheotherplayers.

However,inpsychologicalgamesmodels,payoffsareallowedtodependdirectlyupon

player’sbeliefs,theirbeliefsabouttheircoplayers’beliefs,andsoon,adependencethatis

ruledoutinstandardgametheory.Theincorporationofbelief‐dependentmotivations

makesitpossibletocaptureconcernsaboutintentions,socialimage,orevenemotionsina

game‐theoreticframework.Forexample,inpsychologicalgamesoneperson,Conor(C)

mightbedelightedtobesurprisedbytheactionofanotherplayer,Lexie(L).Thisis

modeledmathematicallyasClikingwhenL’sstrategyisdifferentthanwhathe(C)

expectedLtodo.Someofthesemotivationsarenaturallyconstruedassocialemotions,

suchasguilt(e.g.,apersonfeelsbadchoosingastrategywhichharmedanotherpersonP

whodidnotexpectit,andfeelslessbadifPdidexpectit).

Ofthetwoapproaches,CHandlevel‐kmodelingareeasytouseandapplyto

empiricalsettings.Psychologicalgamesaremoregeneral,applyingtoabroaderclassof

games,butaremoredifficulttoadapttoempiricalwork.

II.TheCHmodel

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Thenextsectionwillgivessomemotivatingempiricalexamplesofthewidescopeof

gamestowhichthetheoryhasbeenappliedwithsomesuccess(includingtwokindsoffield

data),andconsistencywithdataonvisualfixationandfMRI.TheCHapproachisappealing

asapotentialcognitivealgorithmforfourreasons:

1. Itappearstofitalotofexperimentaldatafrommanydifferentgamesbetter

thanequilibriumpredictionsdo(e.g.,Camereretal.,2004;Crawford,Costa‐

Gomes,&Iriberri,2010).

2. Thespecificationofhowthinkingworksandcreateschoicesinvites

measurementofthethinkingprocesswithresponsetimes,visualfixationson

certainpayoffs,andtransitionsbetweenparticularpayoffs.

3. TheCHapproachintroducesaconceptofskillintobehavioralgametheory.

IntheCHmodel,theplayerswiththehighestthinkinglevels(higherk)and

mostresponsivechoices(higherλ)areimplicitlymoreskilled.(In

equilibriummodels,allplayersareperfectlyandequallyskilled.)

NextwewilldescribeseveralempiricalgamesthatillustratehowCHreasoning

works.

Example1:p‐beautycontest

AsimplegamethatillustratesapparentCHthinkinghascometobecalledthe“p‐

beautycontestgame”(orPBC).ThenamecomesfromafamouspassageinJohnMaynard

Keynes’sbookTheGeneralTheoryofEmployment,InterestandMoney.Keyneswrote:

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“Professionalinvestmentmaybelikenedtothosenewspapercompetitionsinwhich

thecompetitorshavetopickoutthesixprettiestfacesfromahundredphotographs,

theprizebeingawardedtothecompetitorwhosechoicemostnearlycorrespondsto

theaveragepreferencesofthecompetitorsasawhole;sothateachcompetitorhas

topick,notthosefaceswhichhehimselffindsprettiest,butthosewhichhethinks

likeliesttocatchthefancyoftheothercompetitors,allofwhomarelookingatthe

problemfromthesamepointofview.Itisnotacaseofchoosingthosewhich,tothe

bestofone'sjudgment,arereallytheprettiest,noreventhosewhichaverage

opiniongenuinelythinkstheprettiest.Wehavereachedthethirddegreewherewe

devoteourintelligencestoanticipatingwhataverageopinionexpectstheaverage

opiniontobe.Andtherearesome,Ibelieve,whopractisethefourth,fifthandhigher

degrees.”

IntheexperimentalPBCgamepeoplechoosenumbersfrom0to100simultaneously

withouttalking.vThepersonwhosenumberisclosesttoptimestheaveragewinsafixed

price.

Atypicalinterestingvalueofpis2/3.Thenthewinnerwantstobetwo‐thirdsofthe

waybetweentheaverageandzero.Butofcourse,theplayersallknowtheotherplayers

wanttopick2/3oftheaverage.InaNashequilibrium,everyoneaccuratelyforecaststhat

theaveragewillbeX,andalsochoosesanumberwhichis(2/3)X.ThisimpliesX=(2/3)Xor

X*=0.

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Intuitively,supposeyouhadnoideawhatotherpeoplewoulddo,soyouchose2/3

of50=33.Thisisareasonablechoicebutisnotanequilibrium,sincechoosing33while

anticipating50leavesagapbetweenexpectedbehaviorofothersandlikelybehaviorby

oneself.Soapersonwhothinks“Hey!I’llpick33”shouldthenthink(toadheretothe

equilibriummath)“Hey!They’llpick33”andthenpick22.Thisprocessofimagining,

choosingandrevisingdoesnotstopuntileveryoneexpects0tobechosen,andalsopicks0.

Figure1showssomedatafromthisgameplayedwithexperimentalsubjectsandin

newspaperandmagazinecontests(wherelargegroupsplayforasinglelargeprize).There

issomeevidenceof“spikes”innumberscorrespondingto50p,50p2andsoon.

Example2:Bettingonselfishrationalityofothers

AnothersimpleillustrationoftheCHtheoryisshowninTable1.Inthisgamearow

andcolumnplayerchoosefromoneoftwostrategies,TorB(forrow)orLorR(for

column).Thecolumnplayeralwaysgets20forchoosingLand18forchoosingR.Therow

playergetseither30or10fromT,andasure20fromB.

Ifthecolumnplayeristryingtogetthelargestpayoff,sheshouldalwayschooseL(it

guarantees20insteadof18).ThestrategyLiscalleda“strictlydominantstrategy”because

ithasthehighestpayoffforeverypossiblechoicebytherowplayer.

Therowplayer’schoiceisalittletrickier.Shecanget20forsurebychoosingB.

ChoosingTistakingasocialgamble.Ifsheisconfidentthecolumnplayerwilltrytoget20

andchooseL,sheshouldinferthatP(L)ishigh.ThentheexpectedvalueofTishighandshe

shouldchooseT.However,thisinferenceisessentiallyabetontheselfishrationalityofthe

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otherplayer.Therowplayermightthinkthecolumnplayerwillmakeamistake,oris

spiteful(andprefersthe(10,18)cellbecauseshegetslessabsolutepayoffbutahigher

relativepayoffcomparedtotherowplayer).Thereisacrucialcognitivedifferencein

playingL—whichistherightstrategyifyouwantthemostmoney—andplayingT—which

istherightstrategyifyouarewillingtobetthatotherplayersareverylikelytochooseL

becausetheywanttoearnthemostmoney.

WhatdoestheCHapproachpredicthere?Supposelevel0playersrandomize

betweenthetwostrategies.Ifτ=1.5,thenf(0|τ=1.5)=.22.Thenhalfofthelevel0players

willchoosecolumnRandrowB,whichis.11%ofthewholegroup.

Level1playersalwayschooseweaklydominantstrategies,sotheypickcolumnL

(infact,allhigherlevelcolumnplayersdotoo).Sincelevel1rowplayersthinkLandR

choicesareequallylikely,theirexpectedpayofffromTis30(.5)+10(.5)=20,whichisthe

sameastheBpayoff;soweassumetheyrandomizeequallybetweenTandB.Since

f(1|τ=1.5)=.33,thismeanstheunconditionaltotalfrequencyofBplayforthefirsttwo

levelsis.11+.33/2=.27.

Level2rowplayersthinktherelativeproportionsoflowertypesare

g2(0)=.22/(.22+.33)=.40andg2(1)=.33/(.22+.33)=.60.Theyalsothinkthelevel0’splay

eitherLorR,butthelevel1’schooseLforsure.Together,thisimpliesthattheybelieve

thereisa.20chancetheotherpersonwillchooseR(=.5(.40)+0(.60))andan.80chance

theywillchooseL.Withtheseodds,theyprefertochooseT.Thatis,theyaresufficiently

confidenttheotherplayerwill“figureitout”andchoosetheself‐servingLthatTbecomesa

goodbettoyieldthehigherpayoffof30.

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Puttingtogetherallthefrequenciesf(k)andchoicepercentages,theoverall

expectedproportionofcolumnRplayis.11androwBplayis.27.Notethatthese

proportionsgointhedirectionoftheNashprediction(whichiszeroforboth),butaccount

morepreciselyforthechanceofmistakesandmisperceptions.Importantly,choicesofR

shouldbelesscommonthanchoicesofB.Rchoicesarejustcareless,whileBchoicesmight

becarelessormightbesensibleresponsestothinkingtherearealotofcarelessplayers.

Table1showsthatsome(unpublished)datafromCaltechundergraduateclassroom

games(formoney)overthreeyearsaregenerallyclosetotheCHprediction.TheRandB

choicefrequenciesaresmall(asbothNashandCHpredict)butBismorecommonthanR.

[InsertTable1abouthere]

OnepotentialadvantageofCHmodelingisthatthesamegeneralprocesscould

applytogameswithdifferenteconomicstructures.Inbothofthetwoexamplesabove,a

Nashequilibriumchoicecanbederivedbyrepeatedapplicationoftheprincipleof

eliminating“weaklydominated”strategies(i.e.,strategieswhichareneverbetterthan

anotherdominatingstrategy,forallchoicesbyotherpeople,andisactuallyworseforsome

choicesbyothers).Hence,thesearecalled“dominancesolvable”games.Indeed,the

beauty‐contestexampleisamongthosethatmotivatedCHmodelinginthefirstplace,since

eachstepofreasoningcorrespondstoonemorestepindeletionofdominatedstrategies.

Hereisanentirelydifferenttypeofgame,called“asymmetricmatchingpennies”.In

thisgametherowplayerearnspointsifthechoicesmatch(H,H)or(T,T).Thecolumn

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playerwinsiftheymismatch.Thereisnopairofstrategiesthatarebestresponsestoeach

other,sotheequilibriumrequireschoosingaprobabilistic“mixture”ofstrategies.Here,

equilibriumanalysismakesabizarreprediction:TherowplayershouldchooseHandT

equallyoften,whilethecolumnplayershouldshyawayfromH(asifpreventingRowfrom

gettingthebiggerpayoffof2)andchooseT2/3ofthetime.(Evenmorestrangely:Ifthe2

payoffisx>1ingeneral,thenthemixtureisalways50‐50fortherowplayer,andisx/(x+1)

onTforthecolumnplayer!Thatis,intheorychangingthepayoffof2onlyaffectsthe

columnplayer,anddoesnotaffecttherowplayerwhomightearnthatpayoff.

TheCHapproachworksdifferentlyvi.Thelowerlevelrowplayers(1‐2)areattracted

tothepossiblepayoffof2,andchooseH.However,thelowlevelcolumnplayersswitchto

T,andhigherlevelrowplayers(levels3‐4)figurethisoutandswitchtoT.Thepredicted

mixture(fortau=1.5)isactuallyratherclosetotheNashpredictionforthecolumnplayer

(P(T)=.74comparedtoNash.67),sincethehigher‐leveltypeschooseTmoreandnotH.

Andindeed,datafromcolumnplayerchoicesinexperimentsareclosetobothpredictions.

TheCHmixtureofrowplay,averagedacrosstypefrequencies,isP(H)=.68,closetothedata

averageof.72.Thus,thereasonablepartoftheNashprediction,whichislopsidedplayofT

andHbycolumnplayers,isreproducedbyCHandisconsistentwiththedata.The

unreasonablepartoftheNashprediction,thatrowplayerschooseHandTequallyoften,is

notreproducedandthedifferingCHpredictionismoreempiricallyaccurate.

[InsertTable2abouthere]

Entrygames

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Insimple“entry”games,Nplayerssimultaneouslychoosewhethertoentera

marketwithdemandC,ornot.Iftheystayout,theyearnafixedpayoff($.50).Iftheyenter,

thenalltheentrantsearn$1ifthereareCorfewerentrants,andearn0iftherearemore

thanCentrants.ItiseasytoseethattheequilibriumpatternofplayisforexactlyCpeople

toenter;thentheyeachearn$1andthosewhostayoutearn$.50.Ifoneofthestayer‐

outersswitchedandentered,shewouldtipthemarketandcausetheC+1entrantstoearn

0.Sincethiswouldlowerherownpayoff,shewillstayput.Sothepatternisanequilibrium.

However,thereisaproblemremaining(it’sacommononeingametheory):How

doesthegroupcollectivelydecide,withouttalking,whichoftheCpeopleenterandearn

$1?EverybodywouldliketobeintheselectgroupofCentrantsiftheycan;butiftoomany

entertheyallsuffer.viiThisisafamiliarproblemof“coordinating”toreachoneofmany

differentequilibria.

Thefirstexperimentsonthistypeofentrygameweredonebyateamofeconomists

(JamesBranderandRichardThaler)andapsychologist,DanielKahneman.Theywere

neverfullypublishedbutweredescribedinachapterbyKahneman(1988).Kahneman

saystheywereamazedhowclosethenumberoftotalentrantswastotheannounced

demandC(whichvariedovertrials).“Toapsychologist”,hewrote,“itlookedlikemagic”.

Sincethen,acoupleofdozenstudieshaveexploredvariantsofthesegamesandreported

similardegreesofcoordination(e.g.,Duffy&Hopkins,2005).

Let’sseeifcognitivehierarchycanproducethemagic.Supposelevel0playersenter

andstayoutequallyoften,andignoreC.Iflevel1playersanticipatethis,theywillthink

therearetoomanyentrantsforC<(N/2)andtoofewifC>(N/2)‐1.Level1playerswill

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thereforeenterathighvaluesofC.Noticethatlevel1playersarehelpingthegroupmove

towardtheequilibrium.Level1’sundothedamagedonebythelevel0’s,whoover‐enterat

lowC,bystayingoutwhichreducestheoverallentryrateforlowC.Theyalsoexploitthe

opportunitythatremainsforhighC,byentering,whichincreasestheoverallentryrate.

Combiningthetwolevels,therewillbelessentryatlowCandmoreentryathighC(itwill

looklikeastepfunction;seeCamereretal.,2004).

Furthermore,itturnsoutthataddinghigher‐levelthinkerscontinuestopushthe

populationprofiletowardanoverallentrylevelthatisclosetoC.Thetheorymakesthree

sharppredictions:(1)Plottingentryrates(asa%ofN)againstC/Nshouldyielda

regressivelinewhichcrossesat(.5,.5).(2)EntryratesshouldbetoohighforC/N<.5and

toolowforC/N>.5.(3)EntryshouldbeincreasinginC,andrelativelyclose,evenwithout

anylearningatall!(e.g.,inthefirstperiodofthegame).

Figure3illustratesaCHmodelpredictionwithτ=1.25,single‐perioddatawithno

feedbackfromCamereretal.(2004),andtheequilibrium(a45‐degreeline).Exceptfor

somenonmonotonicdipsintheexperimentaldata(easilyaccountedforbysampling

error),thepredictionsareroughlyaccurate.

Thepointofthisexampleisthatapproximateequilibrationcanbeproduced,asifby

“magic”,purelyfromcognitivehierarchythinkingwithoutanylearningorcommunication

needed.Thesedataarenotsolidproofthatcognitivehierarchyreasoningisoccurringin

thisgame,butdoesshowhow,inprinciple,thecognitivehierarchyapproachcanexplain

bothdeviationsfromNashequilibrium(inthebeautycontest,betting,andmatching

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penniesgamesthatweredescribedabove),andalsosurprisingconformitytoNash

equilibrium(inthisentrygame).

Privateinformation

Thetrickiestclassofgameswewilldiscuss,briefly,involve“privateinformation”.

Thestandardmodelingapproachistoassumethereisahiddenvariable,X,whichhasa

possibledistributionp(X)thatiscommonlyknowntobothplayersviii.TheinformedplayerI

knowstheexactvaluexfromthedistributionandbothplayersknowthatonlyIknowsthe

value.Forexample,incardgameslikepoker,playersknowthepossiblesetofcardstheir

opponentmighthave,andknowthattheopponentknowsexactlywhatthecardsare.

Thecognitivechallengethatisspecialtoprivateinformationgamesistoinferwhat

aplayer’sactions,whethertheyareactuallytakenorhypothetical,mightrevealabouttheir

information.Variousexperimentalandfielddataindicatethatsomeplayersarenotvery

goodatinferringhiddeninformationfromobservedaction(oranticipatingtheinferable

information).

Asimpleandpowerfulexampleisthe“acquire‐a‐company”problemintroducedin

economicsbyAkerlof(1970)andstudiedempiricallybyBazermanandSamuelson(1983).

Inthisgame,aprivately‐heldcompanyhasavaluewhichisperceivedbyoutsiderstobe

uniformlydistributedfrom0to100(i.e.,allvaluesinthatrangeareequallylikely).The

companyknowsitsexactvalue,andoutsidersknowthatthecompanyknows(duetothe

commonpriorassumption).

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Abiddercanoperatethecompanymuchbetter,sothatwhateverthehiddenvalueV

is,itisworth1.5Vtothem.Theymakeatake‐it‐or‐leave‐it(Boulwarean)offerofapriceP.

Thebargainingcouldhardlybesimpler:ThecompanysellsifthepricePisabove“hidden”

valueV—whichthebidderknowsthatthecompanyknows—andkeepsthecompany

otherwise.Thebidderwantstomaximizetheexpected“surplus”gainbetweentheaverage

ofthevalues1.5Vtheyarelikelytoreceiveandtheprice.

Whatwouldyoubid?Theoptimalbidissurprising,thoughthealgebrabehindthe

answerisnottoohard.ThechanceofgettingthecompanyisthechancethatVislessthan

P,whichisP/100(e.g.,ifP=60then60%ofthetimethevalueisbelowPandthecompany

changeshands).Ifthecompanyissold,thenthevaluemustbebelowP,sotheexpected,

valuetotheselleristheaverageofthevaluesintheinterval[0,P],whichisP/2.Thenet

expectedvalueistherefore(P/100)timesexpectedprofitifsold,whichis1.5*(P/2)‐P=

‐1/4P.Thereisnowaytomakeaprofitonaverage.Theoptimalbidiszero!

However,typicaldistributionsofbidsarebetween50and75.Thisresultsina

“winner’scurse”inwhichbidders“win”thecompany,butfailtoaccountforthefactthat

theyonlywonbecausethecompanyhadalowvalue.Thisphenomenonwasfirstobserved

infieldstudiesofoil‐leasebidding(Capenetal1971)andhasbeenshowninmanylaband

fielddatasetssincethen.Thegeneralprinciplethatpeoplehaveahardtimeguessingthe

implicationsofprivateinformationforactionsotherswilltakeshowsupinmanyeconomic

settings(akindofstrategicnaivete;e.g.Brocasetal.,2009).

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TheCHapproachcaneasilyexplainstrategicnaiveteasaconsequenceoflevel1

behavior.Iflevel1playersthinkthatlevel0players’choicesdonotdependonprivate

information,thentheywillignorethelinkbetweenchoicesandinformation.

Eyetrackingevidence

Apotentialadvantageofcognitivehierarchyapproachesisthatcognitivemeasures

associatedwiththealgorithmicstepsplayersareassumedtouse,intheory,couldbe

collectedalongwithchoices.Forpsychologiststhisisobviousbut,amazingly,itisarather

radicalpositionineconomicsandmostareasofgametheory!

Theeasiestandcheapestmethodistorecordwhatinformationpeoplearelooking

atastheyplaygames.Eyetrackingmeasuresvisualfixationsusingvideo‐basedeyetracking,

typicallyevery5‐50msec.Cameraslookintotheeyeandadjustforheadmotiontoguess

wheretheeyesarelooking(usuallywithexcellentprecision).Mosteyetrackersrecord

pupildilationaswell,whichisusefulasameasureofcognitivedifficultyorarousal.

Sincegametheoryisaboutinteractionsamongtwoormorepeople,itisespecially

usefultohavearecordingtechnologythatscalesuptoenablerecordingofseveralpeople

atthesametime.Onewidely‐usedmethodiscalled“Mouselab”.InMouselab,information

thatisusedinstrategiccomputations,intheory,ishiddeninlabeledboxes,which“open

up”whenamouseismovedintothem.ix

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Severalstudieshaveshownthatlookuppatternsoftencorrespondroughly,and

sometimesquiteclosely,todifferentnumbersofstepsofthinking.We’llpresentone

example(seealsoCrawfordetal.,2010).

Example1:Alternating‐offerbargaining

Apopularapproachtomodelingbargainingistoassumethatplayersbargainovera

knownsumofjointgain(sometimescalled“surplus”,likethevaluablegapbetweenthe

highestpriceabuyerwillpayandthelowestpriceasellerwillaccept).However,astime

passestheamountofjointgain“shrinks”duetoimpatienceorothercosts.Players

alternatemakingoffersbackandforth(Rubinstein,1982).

Athree‐periodversionofthisgamehasbeenstudiedinmanyexperiments.The

amountdividedinthefirstroundis$5,whichthenshrinksto$2.50,$1.25,and0inlater

rounds(thelastroundisan“ultimatumgame”).Ifplayersareselfishandmaximizetheir

ownpayoffs,andbelievethatothersaretoo,the“subgameperfect”equilibrium(SPE)offer

bythefirstpersonwhooffers(player1),toplayer2,shouldbe$1.25.However,deriving

thisoffereitherrequiressomeprocessoflearningorcommunication,orananalysisusing

“backwardinduction”todeducewhatofferswouldbemadeandacceptedinallfuture

rounds,thenworkingbacktothefirstround.Earlyexperimentsshowedconflictingresults

inthisgame.Neelinetal.(1988)foundthataverageofferswerearound$2,andmanywere

equalsplitsof$2.50each.Earlier,Binmoreetal.(1985)foundsimilarresultsinthefirst

roundofchoices,butalsofoundthatasmallamountofexperiencewith“rolereversal”

(player2’sswitchingtotheplayer1first‐offerposition)movedofferssharplytowardthe

SPEofferof$1.25.Otherevidencefromsimplerultimatumgamesshowedthatpeopleseem

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tocareaboutfairness,andarewillingtorejecta$2offeroutof$10abouthalfthetime,to

punishabargainingpartnertheythinkhasbeenunfairandgreedy(Camerer,2003).

Soaretheoffersaround$2duetocorrectanticipationoffairness‐influenced

behavior,ortolimitedunderstandingofhowthefutureroundsofbargainingmightshape

reactionsinthefirstround?Tofindout,Camereretal.(1993)andJohnsonetal.(2002)did

thesametypeofexperiment,buthidtheamountsbeingbargainedoverineachroundin

boxesthatcouldbeopened,or“lookedup”,bymovingamouseintothoseboxes(an

impoverishedexperimenter’sversionofvideo‐basedeyetracking).Theyfoundthatmost

peoplewhoofferedamountsbetweentheequalsplitof$2.50andtheSPEof$1.25werenot

lookingaheadatpossiblefuturepayoffsasbackwardinductionrequires.Infact,in10‐20%

ofthetrialstheround2andround3boxeswerenotopenedatall!

Figure4illustratesthebasicresults.Thetoprectangular“icongraphs”visually

representtherelativeamountsoftimebargainersspentlookingateachpayoffbox(the

shadedarea)andnumbersofdifferentlookups(rectanglewidth).Theboldarrowsindicate

therelativenumberoftransitionsfromoneboxtothenext(withaveragesoflessthanone

transitionomitted).

Eachcolumnrepresentsagroupoftrialsthatarepre‐classifiedbylookuppatterns.

Thefirstcolumn(N=129trials)averagespeoplewholookedmoreoftenattheperiod1box

thanatthefutureperiodboxes(indicating“level‐0”planning).Thesecondcolumn(N=84)

indicatespeoplewholookedlongeratthesecondboxthanthefirstandthird(indicating

“levelOne”planningwithsubstantialfocusonestepahead).Thethirdcolumn(N=27)

indicatesthesmallernumberof“equilibrium”trialsinwhichthethirdboxislookedatthe

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most.NotethatinthelevelOneandEquilibriumtrials,therearealsomanytransitions

betweenboxesoneandtwo,andboxestwoandthree,respectively.Finally,thefourthand

lastcolumnshowspeoplewhowerebrieflytrainedinbackwardinduction,thenplayeda

computerizedopponentthat(theyweretold)plannedahead,actedselfishlyandexpected

thesamefromitsopponents.

Themainpatterntonoticeisthatofferdistributions(shownatthebottomofeach

column)shiftfromright(fairer,indicatedbytherightdottedline)toleft(closertoselfish

SPE,theleftdottedline)asplayersliterallylookaheadmore.Thelinkbetweenlookupsand

higher‐than‐predictedoffersclearlyshowsthatoffersabovetheSPE,inthedirectionof

equalsplitsofthefirstroundamount,arepartlyduetolimitsonattentionandcomputation

aboutfuturevalues.Eveninthefewequilibriumtrials,offersarebimodal,clusteredaround

$1.25and$2.20.However,offersarerathertightlyclusteredaroundtheSPEpredictionof

$1.25inthe“trained”condition.Thisresultindicates,importantly,thatbackwardinduction

isnotactuallythatcognitivelychallengingtoexecute(afterinstruction,theycaneasilydo

it),butinsteadisanunnaturalheuristicthatdoesnotreadilyspringtothemindsofeven

analyticalcollegestudents.

fMRIevidence

Severalneuralstudieshaveexploredwhichbrainregionsaremostactivein

differenttypesofstrategicthinking.Theearlieststudiesshoweddifferentialactivation

whenplayingagameagainstacomputercomparedtoarandomizedopponent(e.g.,

(Gallagheretal.,2002;McCabeetal.,2001;Coricelli&Nagel,2009).

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Oneofthecleanestresults,andanexemplarofthecompositepictureemergingfrom

otherstudies,isfromCoricelli&Nagel’s(2009)studyofthebeautycontestgame.Their

subjectsplayed13differentgameswithdifferenttargetmultipliersp(e.g.,p=2/3,1,3/2

etc.).Oneachtrial,subjectschosenumbersintheinterval[0,100]playingagainsteither

humansubjectsoragainstarandomcomputeropponent.Usingbehavioralchoices,most

subjectscanbeclassifiedintoeitherlevel1(n=10;choosingptimes50)orlevel2(n=7;

choosingptimesptimes50,asifanticipatingtheplayoflevel1opponents).

Figure7showsbrainareasthatweredifferentiallyactivewhenplayinghuman

opponentscomparedtocomputeropponents,andinwhichthathuman‐computer

differentialislargerinlevel2playerscomparedtolevel1players.Thecrucialareasare

bilateraltemporo‐parietaljunction(TPJ),MPFC/paracingulateandVMPFC.xTheseregions

arethoughttobepartofageneralmentalizingcircuit,alongwithposteriorcingulate

regions(Amodio&Frith,2006).

Inrecentstudies,atleastfourareasarereliablyactivatedinhigher‐levelstrategic

thinking:dorsomedialprefrontalcortex(DMPFC),precuneus/posteriorcingulate,insula,

anddorsolateralprefrontalcortex(DLPFC).Nextwesummarizesomeofthesimplest

results.

DMPFCactivityisevidentinFigure7.Itisalsoactiveinresponsetononequilibrium

choices(wheresubjects’guessesaboutwhatotherswilldoarewrong;Bhatt&Camerer,

2005),anduncertaintyaboutstrategicsophisticationofanopponent(Yoshidaetal.,2009).

Inaddition,DMPFCactivityisrelatedtothe“influencevalue”ofcurrentchoicesonfuture

rewards,filteredthroughtheeffectofaperson’sfuturechoicesonanopponent’sfuture

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choices(Hampton,Bossaerts,&O’Doherty,2009;a/k/a“strategicteaching”Camerer,Ho

andChong2002).Amodio&Frith(2006)suggestanintriguinghypothesis:that

mentalizing‐valueactivationforsimplertomorecomplexactionvaluecomputationsare

differentiallylocatedalongaposterior‐to‐anterior(back‐to‐front)gradientinDMPFC.

Indeed,thelatterthreestudiesshowactivationroughlyinaposterior‐to‐anteriorgradient

(Tailarachy=36,48,63;andy=48inCoricelli&Nagel,2009)thatcorrespondstoincreasing

complexity.

Activityintheprecuneus(adjacenttoposteriorcingulate)isassociatedwith

economicperformanceingames(“strategicIQ”;Bhatt&Camerer2005)anddifficultyof

strategiccalculations(Kuoetal.2009).Precuneusisabusyregion,withreciprocal

connectionstoMPFC,cingulate,andDLPFC.Itisalsoactivatedbyawidevarietyofhigher‐

ordercognitions,includingperspective‐takingandattentionalcontrol(aswellasthe

“defaultnetwork”activeatrest;seeBhatt&Camerer,inpress).Itislikelythatprecuneusis

notactivatedinstrategicthinking,perse,butonlyinspecialtypesofthinkingwhich

requiretakingunusualperspectives(e.g.,thinkingaboutwhatotherpeoplewilldo)and

shiftingmentalattentionbackandforth.

Theinsulaisknowntobeinvolvedininteroceptiveintegrationofbodilysignalsand

cognition.Disgust,physicalpain,empathyforothersinpain,andpainfromsocialrejection

activateinsula(Eisenbergeretal.2003,Krossetal.2011).Financialuncertainty

(Preuschoff,Quartz,Bossaerts,2008),interpersonalunfairness(Sanfeyetal.,2003;Hsuet

al.,2008),avoidanceofguiltintrustgames(Changetal.,2011),and“coaxing”orsecond‐

trysignalsintrustgamesalsoactivateinsula.Instrategicstudies,BhattandCamerer

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(2005)foundthathigherinsulaactivityisassociatedwithlowerstrategicIQ

(performance).

TheDLPFCisinvolvedinworkingmemory,goalmaintenance,andinhibitionof

automaticprepotentresponses.Differentialactivitythereisalsoassociatedwiththelevel

ofstrategicthinking(Yoshidaetal.,2009)withstrongerresponsetohumanopponentsin

higher‐levelstrategicthinkers(Coricelli&Nagel,2009),andwithmaintaininglevel‐2

deceptioninbargaininggames(Bhattetal.,2009).xi

Dothinkingstepsvarywithpeopleorgames?

Towhatextentdostepsofthinkingvarysystematicallyacrosspeopleorgame

structures?Fromacognitivepointofview,itislikelythatthereissomeintrapersonal

stabilitybecauseofdifferencesinworkingmemory,strategicsavvy,exposuretogame

theory,experienceinsportsbettingorpoker,taskmotivation,etc.However,itisalsolikely

thattherearedifferencesinthedegreeofsophistication(measuredbyτ)acrossgames

becauseofaninteractionbetweengamecomplexityandworkingmemory,orhowwellthe

surfacegamestructuremapsontoevolutionarilyfamiliargamesxii.

Todate,thesesourcesofleveldifferenceshavenotbeenexploredverymuch.Chong,

HoandCamerer(2005)notesomeeducationaldifferences(Caltechstudentsareestimated

todo.5stepsofthinkingmorethansubjectsfromanearbycommunitycollege)andan

absenceofagendereffect.Otherstudieshaveshowedmodestassociations(r=.3)between

strategiclevelsandworkingmemory(digitspan;Devetag&Warglien,2003)andthe“eyes

ofthemind”testofemotiondetection(Georganas,Healy,&Weber2010).

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Manypapershavereportedsomedegreeofcross‐gametypestabilityinlevel

classification.Studiesthatcompareachoiceinonegamewithonedifferentgamereport

lowstability(Georganasetal.,2010;Burchardi&Penczynski2010).However,asiswell‐

knowninpersonalitypsychologyandpsychometrics,intrapersonalreliabilitytypically

increaseswiththenumberofitemsusedtoconstructascale.Otherstudiesusingmore

gamechoicestoclassifyreportmuchhighercorrelations(comparabletoBig5personality

measures)(Bhui&Camerer,2011).

Asoneillustrationofpotentialtype‐stability,Figure5belowshowsestimatedtypes

forindividualsusingthefirst11gamesina22‐gameseries(x‐axis)andtypesforthesame

individualsusingthelast11games.Thecorrelationisquitehigh(r=.61).Thereisalsoa

slightupwarddriftacrossthegames(theaveragelevelishigherinthelast11games

comparedtothefirst),consistentwithatransferorpracticeeffect,eventhoughthereisno

feedbackduringthe22games(seealsoWeber,2003).

Fielddata

Sincecontrolledexperimentationcamelatetoeconomics(c.1960)comparedto

psychology,thereisalong‐standingskepticismaboutwhethertheoriesthatworkinsimple

labsettingsgeneralizetonaturally‐ocurringeconomicactivity.Fivestudieshaveapplied

CHorlevel‐kmodelingtoauctions(Gillen,2009),strategicthinkinginmanagerialchoices

(GoldfarbandYang,2009;GoldfarbandXiao,inpress),andboxofficereactionwhen

moviesarenotshowntocriticsbeforerelease(Brown,Camerer&Lovallo,2011).

Onestudyisdescribedhereasanexample(Ostlingetal.,2011).In2007the

SwedishLotterycreatedagameinwhichpeoplepay1eurotoenteralottery.Eachpaying

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entrantchoosesaninteger1‐99,999.Thelowestuniquepositiveinteger(hence,the

acronymLUPI)winsalargeprize.

Thesymmetricequilibriumisaprobabilisticprofileofhowoftendifferentnumbers

arechosen(a“mixed”equilibrium).Thelowestnumbersarealwayschosenmoreoften

(e.g.,1ischosenmostoften);therateofdeclineinthefrequencyofchoiceisaccelerating

uptoasharpinflectionpoint(number5513);andtherateofdeclineslowsdownafter

5513.

Figure6showsthedatafromonlythelowest10%ofthenumberrange,from1‐

10,000(highernumberchoicesarerare,asthetheorypredicts).ThepredictedNash

equilibriumisshownbyadottedline—aflat“shelf”ofchoiceprobabilityfrom1to5513,

thenasharpdrop.AfittedversionoftheCHmodelisindicatedbythesolidline.CHcan

explainthelargefrequencyoflownumberchoices(below1500),sincethesecorrespondto

lowlevelsofstrategicthinking(i.e.,peopledon’trealizeeveryoneelseischoosinglow

numberstoo).Sincelevel‐0typesrandomize,theirbehaviorproducestoomanyhigh

numbers(above5000).Sincethelowestandhighestnumbersarechosentoooften

accordingtoCH,comparedtotheequilibriummixture,CHalsoimpliesagapbetween

predictedandactualchoicesintherange2500‐5000.Thisbasicpatternwasreplicatedina

labexperimentwithasimilarstructure.WhiletherearecleardeviationsfromNash

equilibrium,consistentwithevidenceoflimitedstrategicthinking,inourviewtheNash

theorypredictionisnotbadconsideringthatusesnofreeparameters,andcomesfroman

equationwhichiselegantinstructurebutdifficulttoderiveandsolve.

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TheLUPIgamewasplayedinSwedenfor49daysinarow,andresultswere

broadcastonanightlyTVshow.Analysisindicatesanimitate‐the‐winnerfictivelearning

process,sincechoicesononedaymoveinthedirectionof600‐numberrangearoundthe

previousday’swinner.Theresultofthisimitationisthateverystatisticalfeatureofthe

numberschosenmovestowardtheequilibriumacrossthesevenweeks.Forexample,in

thelastweektheaveragenumberis2484,within4%ofthepredictedvalueof2595.

IIIPsychologicalgames

Inmanystrategicinteractions,ourownbeliefsorbeliefsofotherpeopleseemto

influencehowwevalueconsequences.Forexample,surprisingapersonwithawonderful

giftthatisperfectforthemismorefunforeveryonethanifthepersonhadaskedforit.

Someofthatpleasurecomesfromthesurpriseitself.

Thistypeofpatterncanbemodeledasa“psychologicalgame”(Geanakoplos,Pearce

&Stacchetti,1989andBattigalli&Dufwenberg,2009).PGsareanextensionofstandard

gamesinwhichtheutilityevaluationsofoutcomescandependonbeliefsaboutwhatwas

thoughttobelikelytohappen(aswellastypicalmaterialconsequences).Thisapproach

requiresthinkingandreasoningsincethebeliefisderivedfromanalysisoftheother

person’smotives.Togetherthesepapersprovidetoolsforincorporatingmotivationssuch

asintentions,socialnorms,andemotionsintogame‐theoreticmodels.

Emotionsareanimportantbeliefdependentmotivation.Anxiety,

disappointment,elation,frustration,guilt,joy,regret,andshame,amongother

emotions,canallbeconceivedofasbelief‐dependentincentivesormotivationsand

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incorporatedintomodelsofbehaviorusingtoolsfrompsychologicalgametheory.

Oneexampleisguilt:Baumeister,Stillwell,andHeatherton(1994)write:“If

peoplefeelguiltyforhurtingtheirpartners…andforfailingtoliveuptotheir

expectations,theywillaltertheirbehavior(toavoidguilt).”BattigalliandDufwenberg

(2007)operationalizethenotionthatpeoplewillanticipateandavoidguiltintheir

modelofguiltaversion.Intheirmodel,playersderivepositiveutilityfromboth

materialpayoffsandnegativeutilityfromguilt.Playersfeelguiltyiftheirbehavior

disappointsaco‐playerrelativetohisexpectations.xiii

ConsiderFigure8,whichillustratesasimpletrustgame.Player1maychoose

either“Trust”or“Don’t.”Inthefirstcaseplayer1getsthemove,whileafterachoiceof

“Don’t”thegameendsandeachplayergetspayoff1.Ifplayer2getsthemove,she

choosesbetween“Grab”and“Share.”ThepayoffstoGrabare0forplayer1and4for

player2.

ThesubgameperfectequilibriumofthisgameforselfishplayersisforPlayer2to

chooseGrabifshegetsthemovesinceitresultsinahigherpayoffforherthanchoosing

Share.Player1anticipatesthisbehaviorandchoosesDon’ttoavoidreceiving0.Both

playersreceiveapayoffof1,whichisinefficient.

NowsupposethatPlayer2isguiltaverse.Thenherutilitydependsnotonlyonher

materialpayoff,butalsoonhowmuchshe“letsdown”player1relativetohisexpectations.

Letpbetheprobabilitythatplayer1assignsto“Share.”Letp’representPlayer2’s(point)

beliefregardingp,andsupposethat2’spayofffromGrabisthen4‐θp,wheretheta

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representsplayer2’ssensitivitytoguilt.Ifplayer1choosesTrustitmustbethatpis

greaterthan½‐otherwiseplayer1wouldchooseDon’t.Thenifθ≥2,player2willchoose

SharetoavoidtheguiltfromlettingdownPlayer1.Knowingthis,player1willchoose

Trust.Inthisoutcomebothplayersreceive2(insteadof1intheselfishsubgameperfect

equilibrium),illustratinghowguiltaversioncanfostertrustandcooperationwhereselfish

behaviorleadstoinefficiency.

Anumberofexperimentshavestudiedguiltaversioninthecontextoftrustgames,

includingDufwenberg&Gneezy(2000),Charness&Dufwenberg(2006,2011),and

Reubenetal.(2009).Allofthesepapersfindevidencethatadesiretoavoidguiltmotivates

playerstobehaveunselfishlybyreciprocatingtrust(foracontraryopinionseeEllingsenet

al.,2010).RecentfMRIevidence(Changetal,inpress)suggeststhatavoidingguiltintrust

gamesisassociatedwithincreasedactivityintheanteriorinsula.

Psychologicalgametheoryalsomaybeemployedtomodelothersocialemotions

suchasshame(Tadelis,2008)oranger(Smith,2009)ortoimportexistingmodelsof

emotionssuchasdisappointment,elation,regret,andrejoicing(Bell,1982,1986;

Loomes&Sugden,1982,1985)intogames.xivBattigalli&Dufwenberg(2009)provide

someexamplesoftheseapplications.Thesemodelsarejustaglimpseofthepotential

applicationsofpsychologicalgametheorytotheinteractionofemotionandcognitionin

socialinteractions.

Anotherimportantapplicationofpsychologicalgametheoryissociological

concerns,suchasreciprocity(whichmaybedrivenbyemotions).Inanimportantwork,

Rabin(1993)modelsreciprocityviafunctionsthatcaptureaplayer’s“kindness”tohis

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coplayerandtheotherplayer’skindnesstohim.Thesekindnessfunctionsdependonthe

players’beliefsregardingeachother’sactions,andtheirbeliefsabouteachother’sbeliefs.

Dufwenberg&Kirchsteiger(2004)andFalk&Fischbacher(2006)extendRabin’smodelto

sequentialgames.

Psychologicalgametheoryprovidesausefultoolkitforincorporatingpsychological,

social,andculturalfactorsintoformalmodelsofdecision‐makingandsocialinteractions.

Manyapplicationsremaintobediscoveredandtestedviaexperiment.

Conclusions

Comparedtoitsimpactonotherdisciplines,gametheoryhashadlessimpactin

cognitivepsychologysofar.Thisislikelybecausemanyoftheanalyticalconceptsusedto

derivepredictionsabouthumanbehaviordonotseemtocorrespondcloselytocognitive

mechanisms.Somegametheoristshavealsocomplainedaboutthisunrealism.EricVan

Damme(1999)wrote:

Withouthavingabroadsetoffactsonwhichtotheorize,thereisacertaindangerof

spendingtoomuchtimeonmodelsthataremathematicallyelegant,yethavelittle

connectiontoactualbehavior.Atpresentourempiricalknowledgeisinadequate

anditisaninterestingquestionwhygametheoristshavenotturnedmore

frequentlytopsychologistsforinformationaboutthelearningandinformation

processesusedbyhumans.

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Butrecently,anapproachcalledbehavioralgametheoryhasbeendevelopedwhich

usespsychologicalideastoexplainbothchoicesinmanydifferentgames,andassociated

cognitiveandbiological(Camerer2003;Bhatt&Camerer,2011)

Thischapterdiscussedtwoelementsofbehavioralgametheorythatmightbeof

mostinteresttocognitivepsychologists:Thecognitivehierarchyapproach;and

psychologicalgamesinwhichoutcomevaluescandependonbeliefs,oftenaccompaniedby

emotions(e.g.,alowbargainingoffercouldcreateangerifyouexpectedmore,orjoyifyou

expectedless).

Thecognitivehierarchyapproachassumesthatsomeplayerschooserapidlyand

heuristically(“level0”)andhigher‐levelplayerscorrectlyanticipatewhatlower‐level

playersdo.Thetheoryhasbeenusedtoexplainbehaviorinlabgameswhichisbothfar

fromandclosetoequilibjriumindifferentgames,issupportedbyevidencefromvisual

eyetrackingandMouselab,isevidentin“theoryofmind”circuitryduringfMRI,andalsocan

explainsomepatternsinfielddata(suchastheSwedishLUPIlottery).

Researchonpsychologicalgamesislesswelldevelopedempirically,buthasmuch

promiseforunderstandingphenomenalike“socialimage”,normenforcement,how

emotionsarecreatedbysurprises,andtherelationshipbetweenemotion,cognition,and

strategicbehavior.

FutureDirections

Therearealotofopenresearchquestionsinwhichcombiningcognitivescienceand

gametheorywouldbeuseful.Hereareafew:

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1. Canthedistributionofleveltypesbederivedendogeneouslyfrommorebasic

principlesofcognitivedifficultyandperceivedbenefit,orperhapsfrom

evolutionaryconstraintonworkingmemoryandtheoryofmind(e.g.Stahl,1993).

2. CHmodelshavethepotentialtodescribedifferencesinskillorexperience.Skill

arisesineverydaydiscussionsaboutevensimplegameslikerock,paperand

scissors,ingameswithprivateinformationsuchaspoker,andgamesthattax

workingmemorysuchaschess.Areskilldifferencesgeneralordomain‐specific?

Canskillbetaught?Howdoesskilldevelopmentchangecognitionandneural

activity?

3. Thecomputationalapproachtostrategicthinkinginbehavioralgametheorycould

beusefulforunderstandingthesymptoms,etiologyandtreatmentofsome

psychiatricdisorders.Disorderscouldbeconceptualizedasfailurestocorrectly

anticipatewhatotherpeopledoandfeelinsocialinteractions,ortomakegood

choicesgivensensiblebeliefs.Forexample,inrepeatedtrustgamesKing‐Casaset

al.,(2008)foundthatborderlinepersonalitydisorder(BPD)didnothavetypical

activityininsulacortexinresponsetobeingmistrusted,andearnedlessmoney

becauseoftheinabilitytomaintainsteadyreciprocaltrustbehaviorally.Chiu

(2008)foundthatautismpatientshadlessactivityinaregionofanteriorcingulate

thattypicallyencodessignalsofvaluationduringone’sownstrategicchoices

(comparedtochoicesofothers).

4. Asmallemergingapproachinthestudyofliteraturefocusesonthenumberof

mentalstatesthatreaderscantrackandtheireffect(e.g.,Zunshine,2006).One

theoryisthatthreementalstatesareasociallyimportantreasonablenumber(e.g.,

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lovetriangles)andarethereforenarrativelyengaging.Workoncognitiveschemas,

socialcategorization,computationallinguistics,andgametheorycouldthereforebe

ofinterestinthestudyofliterature.

5. Formalmodelsconnectingemotionswithbeliefs,actions,andpayoffscanilluminate

therelationshipsbetweenaffectivestatesandbehavior.Theutilityfunction

approachtomodelingemotionsmakesclearthatemotionsinfluencebehavioronly

whenthehedonicbenefitsofemotionalbehavioroutweighthecosts.Thisapproach,

whichconsidersevenemotion‐drivenbehaviorastheoutcomeofanoptimization

problem(perhapssculptedbyhumanevolutionratherthanconsciouscost‐benefit,

ofcourse).,promisestoopenupnewavenuesofresearchstudyingtherelationship

betweenemotionandstrategicchoices.

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Tablecaptions

Table1:Payoffsinbettinggame,predictions(NashandCH),andresultsfromclassroom

demonstrationsin2006‐08.UpperleftistheuniqueNashequilibrium.

Table2:PayoffsfromHandTchoiceina“matchingpennies”game,predictions,anddata.

Table1:

predictions Data

L R Nash CH 2006+07+08 Average

T 30, 20 10, 18 1.00 .73 .81+.86+.78 .82

B 20, 20 20, 18 .00 .27 .19+.14+.22 .18

Nash 1.00 0

CH .89 .11

2006+07+08 .95+.95+.75 .05+.05+.25

average .88 .12

Table2:

predictions

H T Nash CH Levels

1-2

Levels

3-4

data

H 2,0 0,1 .50 .68 1 0 .72

T 0,1 1,0 .50 .32 0 1 .28

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Nash .33 .67

CH .26 .74

data .33 .67

Figurecaptions

Figure1:Choicesin“2/3oftheaverage”game(Nagel,2005?)

Figure2:Predictedandobservedbehaviorinentrygames

Figure3:ThegameboardfromHeddenandZhang(2002)

Figure4:Anicongraphofvisualattentioninthreeroundsofbargaining(1,2and3)and

correspondingdistributionsofoffers.Eachcolumnrepresentsadifferent“type”ofperson‐

trialclassifiedbyvisualattention.

Figure5:Estimatedstrategicleveltypesforeachindividualintwosetsof11different

games(Chong,Camerer,Ho&Chong,2005).Estimatedtypesarecorrelatedintwosets

(r=.61)

Figure6:Numberschoseninweek1ofSwedishLUPIlottery(Napproximately350,000).

DottedlineindicatesmixedNashequilibrium.Solidlineindicatestochasticcognitive

hierarchy(CH)modelwithtwofreeparameters.Best‐fittingaveragestepsofthinkingisτ

=1.80andλ=.0043(logitresponse).

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Figure7:Brainregionsmoreactiveinlevel2reasonerscomparedtolevel1reasoners

(classifiedbychoices),differentiallyinplayinghumancomparedtocomputeropponents

(fromCoricelliandNagel,2009,FigureS2a).

Figure8:Asimpletrustgame(DufwenbergandGneezy,2008)

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Figure1

Beauty contest results (Expansion, Financial Times, Spektrum)

0.000.050.100.150.20

numbers

rela

tiv

e

fre

qu

en

cie

s

22 50 10033

average 23.07

0

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Figure2

How entry varies with demand (D), experimental data and thinking model

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1

0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8

Demand (as % of # of players)

% e

ntry

entry=demandexperimental data!=1.25

Figure3

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Figure4

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Figure5

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Figure6

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Figure7

Figure8

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iAnotherimportantcomponentofbehavioralgametheoryislearningfromrepeatedplay(perhapsusingreinforcementrulesaswellasmodel‐based“fictivelearning”(Camerer&Ho,1999).Learningmodelsarewidelystudiedbutliebeyondthescopeofthischapter(seee.g.Fudenberg&Levine,1998;Camerer,2003,chapter6).

iiOthermechanismsthatcouldproduceequilibrationincludelearningfromobservation,introspection,calculation(suchasfirmshiringconsultantstoadviseonhowtobidonauctions),imitationofattention‐gettingorsuccessfulstrategiesorpeople,oraprocessofpre‐playtalkingaboutfuturechoices.Thelearningliteratureiswelldeveloped(e.g.,Camerer,2003,chapter6)butthestudyofimitationandpre‐playtalkingcouldcertainlyusemorecollaborationbetweengametheoristsandpsychologists.

iiiCommonknowledgerequires,fortwoplayers,thatAknowsthatBknowsthatAknows…adinfinitum.

ivAmoregeneralviewisthatlevel0’schooseintuitivelyor“heuristically”(perhapsbasedonvisuallysalientstrategiesorpayoffs,or“luckynumbers”),butthattopichasnotbeenexploredverymuch.

vRestrictingcommunicationisnotmeanttoberealisticandcertainlyisnot.Insteadcommunicationisrestrictedbecausechoosingwhattosayisitselfa“strategy”choicewhichcomplicatesanalysisofthegame—itopensaPandora’sboxofpossibleeffectsthatlieoutsidethescopeofstandardgametheory.However,gametheoristsarewellawareofthepossiblepowerfuleffectsofcommunicationandhavebeguntostudyitinsimpleways.InherthesisNagel(1995)reportssomesubjectdebriefingwhichareillustrativeofCHthinking,andSbriglia(2008)reportssomeprotocolstoo.BurchardiandPenczynski(2010)alsousedchatmessagingandteamchoicetostudycommunicationandreportevidencelargelyconsistentwithCHreasoning.

viThisanalysisassumesτ=1.5butthegeneralpointholdsmorewidely.

viiNotethatthisisacloserelativeofa“thresholdpublicgoods”game.Inthatgame,apublicgoodiscreated,whichbenefitseveryone,ifTpeoplecontribute,butifevenoneperson

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doesnotethepublicgoodisnotproduced.Inthatcase,everyonewouldliketobeintheN‐Tgroupofpeoplewhobenefitwithoutpaying.

viiip(X)isa“commonprior.”Anexampleisagameofcards,inwhicheveryoneknowsthecontentsofthecarddeck,donotknowwhatface‐downcardsotherplayersareholding,butalsoknowthattheotherplayersdoknowtheirownface‐downcards.

ixThereareseveralsubtlevariants.IntheoriginalMouselab,boxesopenandcloseautomaticallywhenthemouseentersandexits.Costa‐Gomesetal(2001)wantedmoredeliberateattentionsotheycreatedaversioninwhichaclickisrequiredtoopenabox.Brocasetal(2010)createdaversionthatrequiresthemousebuttontobehelddowntoviewboxcontents(ifthebuttonpressishaltedtheinformationdisappears).

xTherostralACC,labeledrACC,ismoreactiveinlevel1thaninlevel2playersinthehuman‐computercontrast.

xiDLPFCisalsoinvolvedincognitiveregulationofemotions(e.g.,Ochsneretal.,2009)

xiiWhatwehaveinmindhereissimilartoHolyoakandCheng(1985),Fiddick,CosmidesandTooby(2000)argumentsaboutthedifferencebetweenabstractlogicperformanceandcontextualizedperformance.Forexample,gamesthatresemblehidingfoodandguardinghiddenlocationsmightmaproughlyontosomethinglikepoker,whereasalotofgamesconstructedforchallengeandentertainment,suchaschess,donothaveclearcounterpartsinancestraladaptiveenvironments.

xiiiOthermodelsofbelief‐dependentutilitycanbeplacedinthegeneralframeworkofBattigalliandDufwenberg(2009).Forexample,CaplinandLeahy(2004)modeldoctor‐patientinteractionswhereuncertaintymaycausepatientanxiety.Thedoctorisconcernedaboutthepatient’swellbeingandmustdecidewhetherornottoprovide(potentially)anxiety‐causingdiagnosticinformation.Bernheim(1994)proposesamodelofconformitywhereplayerscareaboutthebeliefstheircoplayershaveregardingtheirpreferences.Themodelcanproducefadsandadherencetosocialnorms.RelatedworkbyBenabouandTirole(2006)modelsplayerswhoarealtruistic,andalsocareaboutother’sinferencesabouthowaltruistictheyare.GillandStone(2010)modelplayerswhocareaboutwhattheyfeeltheydeserveintwo‐playertournaments.Theplayers’perceivedentitlementsdependupontheirowneffortlevelandtheeffortsofothers.

xivA(singleperson)decisionprobleminvolvinganyoftheseemotionsmaybemodeledasapsychologicalgamewithoneplayerandmovesbynature.