LEADER 03248oam 22004093a 450 001 9910693954303321 005 20230622022652.0 035 $a(NBER)w14040 035 $a(CKB)3240000000014019 035 $a(EXLCZ)993240000000014019 100 $a20230622d2008 fy 0 101 0 $aeng 135 $aurcnu|||||||| 200 10$aBayesian Learning in Social Networks /$fDaron Acemoglu, Munther A. Dahleh, Ilan Lobel, Asuman Ozdaglar 210 $aCambridge, Mass$cNational Bureau of Economic Research$d2008 215 $a1 online resource$cillustrations (black and white); 225 1 $aNBER working paper series$vno. w14040 300 $aMay 2008. 330 3 $aWe study the perfect Bayesian equilibrium of a model of learning over a general social network. Each individual receives a signal about the underlying state of the world, observes the past actions of a stochastically-generated neighborhood of individuals, and chooses one of two possible actions. The stochastic process generating the neighborhoods defines the network topology (social network). The special case where each individual observes all past actions has been widely studied in the literature. We characterize pure-strategy equilibria for arbitrary stochastic and deterministic social networks and characterize the conditions under which there will be asymptotic learning -- that is, the conditions under which, as the social network becomes large, individuals converge (in probability) to taking the right action. We show that when private beliefs are unbounded (meaning that the implied likelihood ratios are unbounded), there will be asymptotic learning as long as there is some minimal amount of "expansion in observations". Our main theorem shows that when the probability that each individual observes some other individual from the recent past converges to one as the social network becomes large, unbounded private beliefs are sufficient to ensure asymptotic learning. This theorem therefore establishes that, with unbounded private beliefs, there will be asymptotic learning an almost all reasonable social networks. We also show that for most network topologies, when private beliefs are bounded, there will not be asymptotic learning. In addition, in contrast to the special case where all past actions are observed, asymptotic learning is possible even with bounded beliefs in certain stochastic network topologies. 410 0$aWorking Paper Series (National Bureau of Economic Research)$vno. w14040. 606 $aNoncooperative Games$2jelc 606 $aSearch ? Learning ? Information and Knowledge ? Communication ? Belief ? Unawareness$2jelc 615 7$aNoncooperative Games 615 7$aSearch ? Learning ? Information and Knowledge ? Communication ? Belief ? Unawareness 686 $aC72$2jelc 686 $aD83$2jelc 700 $aAcemoglu$b Daron$0126088 701 $aDahleh$b Munther A$01367212 701 $aLobel$b Ilan$01367213 701 $aOzdaglar$b Asuman$0497087 712 02$aNational Bureau of Economic Research. 801 0$bMaCbNBER 801 1$bMaCbNBER 906 $aBOOK 912 $a9910693954303321 996 $aBayesian Learning in Social Networks$93389958 997 $aUNINA LEADER 02552nam2 22005053i 450 001 UM10037284 005 20231121125910.0 010 $a8804373024 020 $aIT$b94-2356 100 $a20150521d1994 ||||0itac50 ba 101 | $aita$cita 102 $ait 181 1$6z01$ai $bxxxe 182 1$6z01$an 200 1 $a˜5.2: œElegia di Madonna Fiammetta$aCorbaccio$aConsolatoria a Pino De Rossi$aBuccolicum carmen$aAllegoria mitologica$fGiovanni Boccaccio$g[Elegia] a cura di Carlo Delcorno , [Corbaccio] a cura di Giorgio Padoan$g[Consolatoria] a cura di Giuseppe Chiecchi$g[Bucolicum] a cura di Giorgio Bernardi Perini$g[Allegoria] a cura di Manlio Pastore Stocchi 210 $aMilano$cMondadori$d1994 215 $a1129 p.$d17 cm. 461 1$1001CFI0008470$12001 $aTutte le opere di Giovanni Boccaccio$fa cura di Vittore Branca$v5 500 10$a˜Il œCorbaccio$3BVEE021423$9CFIV008443$988417 500 10$xLAT$aBuccolicum carmen$3SBN0079166$9CFIV008443$9170692 500 10$xITA$aElegia di Madonna Fiammetta$3TO00051846$9CFIV008443$9220062 500 10$xITA$aEpistola consolatoria a Pino de? Rossi$3TSA1369172$9CFIV008443$93642074 700 1$aBoccaccio$b, Giovanni$f <1313-1375>$3CFIV008443$4070$0148906 702 1$aPastore Stocchi$b, Manlio$3CFIV013136 702 1$aBernardi Perini$b, Giorgio$3CFIV024198 702 1$aDelcorno$b, Carlo$f <1938- >$3CFIV094245 702 1$aPadoan$b, Giorgio$3CFIV097608 702 1$aChiecchi$b, Giuseppe$3VEAV023225 790 1$aBokka??o$b, D?ovanni$3BVEV190597$zBoccaccio, Giovanni <1313-1375> 790 1$aBoccace$b, Jean$3CFIV200438$zBoccaccio, Giovanni <1313-1375> 790 1$aBoccacci$b, Giovanni$3SBNV009184$zBoccaccio, Giovanni <1313-1375> 790 1$aBocace$b, Jehan$3SBNV025023$zBoccaccio, Giovanni <1313-1375> 801 3$aIT$bIT-01$c20150521 850 $aIT-RM028 $aIT-RM0290 $aIT-FR0017 899 $aBiblioteca Universitaria Alessandrina$bRM028 899 $aBIBLIOTECA ANGELICA$bRM0290 899 $aBiblioteca umanistica Giorgio Aprea$bFR0017 $eN 912 $aUM10037284 950 2$aBiblioteca umanistica Giorgio Aprea$d 52MAG 9/1222-5.2$e 52FLS0000165185 VMN RS $fA $h20150521$i20150521 977 $a 01$a 06$a 52 996 $aCorbaccio$988417 996 $aEpistola consolatoria a Pino de? Rossi$93642074 996 $aElegia di madonna Fiammetta$9220062 996 $aBuccolicum carmen"$9170692 997 $aUNICAS