集智凯风研读营二材料dumb ai

BotsimprovehumancoordinationinnetworkexperimentsYongrenShiHumanNatureLabYaleUniversity2ShiradoandChristakis.2017.Locallynoisyautonomousagentsimproveglobalhumancoordinationinnetworkexperiments.3Socialnetworkexperimentwithonlinetools

ColorcoordinationgamesonsocialnetworksGoal:allplayersselectadifferentcolorfromlocalneighborsEachplayerisassignedanodetoselectacolor.Playerschangetheirnodecoloranytimetheywantastheyseetheirneighborscolors.Thegameisfinishedwhentherearenoconflictsinnetwork.Evaluation:timerequiredtosolvethecolorconflictsKearnsM,SuriS,MontfortN(2006)AnExperimentalStudyoftheColoringProblemonHumanSubjectNetworks.Science313:824–827.Player’sviewinthegameCommentsfromhumanplayersSomeoneisauselessidiot,andit'snotme.Thisgameisbullshit.Thanksforwastingmytime.I'mgoingtocry.Gotscrewedonthisgame.Foolmeshameonme....youcantgetfooledagain.Iverymuchenjoyedthisgame.Itwasstrange,becauseIfeltpersonallyattachedtotheotherplayersthatIdon'tevenknow,letaloneknowwhethertheyexistornot.Ifeltdependent,becauseIwasrelyingalotonmyteammembers.Ialsofeltindependent,becauseIwasdoingmyownthing.(snip)IfeltlikeIwasintheMatrixandIwastryingtocrackacodeorsomething.I'dprobablyplaythisgameforfree,itwassoenjoyable.Howcanbotsacceleratethecoordinationprocess?Everyplayerchoosesthebestcolorlocally,

butthegameisnotalwayssolved.105sec.“Unresolvable”conflict“Noise”mightimprovesocialcoordination.Designofbots’behaviorEvery1.5secRandom<PrandomPickacolorrandomlyIsthereabettercolortoreducelocalconflicts?ChangetothebettercolorMaintainthecurrentcoloryesyesnonoThreelevelofbehavioralnoisePrandom=0%,10%,and30%Behavioralnoise (0%,10%,30%)Geodesiclocation (random,center,periphery)Howcanbotsacceleratethecoordinationprocess?Experimentdesign(3by3plus2)groupOnlyhumans(control)RandomlocationCentrallocationPeripherallocationFixed-color(extra)ZeronoiseSmallnoiseLargenoiseZeronoiseSmallnoiseLargenoiseZeronoiseSmallnoiseLargenoise#ofhumans2017171717171717171717#ofbots03333333333Bots’location-randomrandomrandomcentercentercenterperipheryperipheryperipherycenterBots’noise-0%10%30%0%10%30%0%10%30%-#ofsessions3020202020202020202020Nsubjects=4,000,Nnetworks=230Thesessionshavingbotswith10%noiseandcentrallocationswerethemostlikelytobesolvedwithintheallotted5min.Bots’noiseBots’locationResultThesessionshavingbotswith10%noiseandcentrallocationswerethemostlikelytobesolvedwithintheallotted5min.Bots’noiseBots’locationResultNoise10%Center129.3sec66.6%86.6%ResultThesessionshavingbotswith10%noiseandcentrallocationswerethemostlikelytobesolvedwithintheallotted5min.103.1s232.4sHoweffectiveisthebotsintervention?Comparisonwithfixed-colortreatment10%-noisebots(localinfo.)Solvablefixedcolors(globalinfo.)Only38.0%sessionscanbesolvedifthecolorsarerandomlyselected.≈Botnoise0%Botnoise10%Botnoise30%Botnoise0%Botnoise10%Botnoise30%EstimatedrateoferrantcolorchangeAccumulatedtimeofunresolvableconflictsperlink(sec)Networkdegree(#neighbors)SessionsofhumansandbotsSessionsofonlyhumansHumanBotPsychologicalimpactsofbotsonhumansHowcanbotsacceleratethecoordinationprocess?Someirrationalbehaviorsincentralbotsmayhelpoursocialcoordination.???upupupupupupupAIimprove