{"id":"https://openalex.org/W2149012756","doi":"https://doi.org/10.1109/cdc.2008.4739167","title":"Convergence of rule-of-thumb learning rules in social networks","display_name":"Convergence of rule-of-thumb learning rules in social networks","publication_year":2008,"publication_date":"2008-01-01","ids":{"openalex":"https://openalex.org/W2149012756","doi":"https://doi.org/10.1109/cdc.2008.4739167","mag":"2149012756"},"language":"en","primary_location":{"id":"doi:10.1109/cdc.2008.4739167","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cdc.2008.4739167","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2008 47th IEEE Conference on Decision and Control","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5012301204","display_name":"Daron Acemo\u011flu","orcid":null},"institutions":[{"id":"https://openalex.org/I63966007","display_name":"Massachusetts Institute of Technology","ror":"https://ror.org/042nb2s44","country_code":"US","type":"education","lineage":["https://openalex.org/I63966007"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Daron Acemoglu","raw_affiliation_strings":["Department of Economics, Massachusetts Institute of Technology, Cambridge, MA, USA"],"affiliations":[{"raw_affiliation_string":"Department of Economics, Massachusetts Institute of Technology, Cambridge, MA, USA","institution_ids":["https://openalex.org/I63966007"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5110629459","display_name":"Angelia Nedi\u0107","orcid":null},"institutions":[{"id":"https://openalex.org/I157725225","display_name":"University of Illinois Urbana-Champaign","ror":"https://ror.org/047426m28","country_code":"US","type":"education","lineage":["https://openalex.org/I157725225"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Angelia Nedic","raw_affiliation_strings":["Department of Industrial and Enterprise Systems Engineering, University of Illinois, Urbana-Champaign, IL, USA"],"affiliations":[{"raw_affiliation_string":"Department of Industrial and Enterprise Systems Engineering, University of Illinois, Urbana-Champaign, IL, USA","institution_ids":["https://openalex.org/I157725225"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5067307504","display_name":"Asuman Ozdaglar","orcid":"https://orcid.org/0000-0002-1827-1285"},"institutions":[{"id":"https://openalex.org/I63966007","display_name":"Massachusetts Institute of Technology","ror":"https://ror.org/042nb2s44","country_code":"US","type":"education","lineage":["https://openalex.org/I63966007"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Asuman Ozdaglar","raw_affiliation_strings":["Department of Electrical Engineering and Computer Science, Massachusetts Institute of Technology, Cambridge, MA, USA"],"affiliations":[{"raw_affiliation_string":"Department of Electrical Engineering and Computer Science, Massachusetts Institute of Technology, Cambridge, MA, USA","institution_ids":["https://openalex.org/I63966007"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5012301204"],"corresponding_institution_ids":["https://openalex.org/I63966007"],"apc_list":null,"apc_paid":null,"fwci":4.1767,"has_fulltext":false,"cited_by_count":47,"citation_normalized_percentile":{"value":0.94370424,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":90,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"1714","last_page":"1720"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12592","display_name":"Opinion Dynamics and Social Influence","score":0.9930999875068665,"subfield":{"id":"https://openalex.org/subfields/3109","display_name":"Statistical and Nonlinear Physics"},"field":{"id":"https://openalex.org/fields/31","display_name":"Physics and Astronomy"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T12592","display_name":"Opinion Dynamics and Social Influence","score":0.9930999875068665,"subfield":{"id":"https://openalex.org/subfields/3109","display_name":"Statistical and Nonlinear Physics"},"field":{"id":"https://openalex.org/fields/31","display_name":"Physics and Astronomy"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10249","display_name":"Distributed Control Multi-Agent Systems","score":0.9868000149726868,"subfield":{"id":"https://openalex.org/subfields/1705","display_name":"Computer Networks and Communications"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10320","display_name":"Neural Networks and Applications","score":0.9803000092506409,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/rule-of-thumb","display_name":"Rule of thumb","score":0.8365828990936279},{"id":"https://openalex.org/keywords/convergence","display_name":"Convergence (economics)","score":0.7571857571601868},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6192936301231384},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.43551886081695557},{"id":"https://openalex.org/keywords/learning-rule","display_name":"Learning rule","score":0.4163041114807129},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.328937292098999},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.20221123099327087},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.17302098870277405},{"id":"https://openalex.org/keywords/economics","display_name":"Economics","score":0.0802692174911499}],"concepts":[{"id":"https://openalex.org/C89246107","wikidata":"https://www.wikidata.org/wiki/Q1398821","display_name":"Rule of thumb","level":2,"score":0.8365828990936279},{"id":"https://openalex.org/C2777303404","wikidata":"https://www.wikidata.org/wiki/Q759757","display_name":"Convergence (economics)","level":2,"score":0.7571857571601868},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6192936301231384},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.43551886081695557},{"id":"https://openalex.org/C2779127903","wikidata":"https://www.wikidata.org/wiki/Q6510194","display_name":"Learning rule","level":3,"score":0.4163041114807129},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.328937292098999},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.20221123099327087},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.17302098870277405},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0802692174911499},{"id":"https://openalex.org/C50522688","wikidata":"https://www.wikidata.org/wiki/Q189833","display_name":"Economic growth","level":1,"score":0.0}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.1109/cdc.2008.4739167","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cdc.2008.4739167","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2008 47th IEEE Conference on Decision and Control","raw_type":"proceedings-article"},{"id":"pmh:oai:CiteSeerX.psu:10.1.1.208.2580","is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.208.2580","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://web.mit.edu/asuman/www/documents/CDCmyopic-learning-submit.pdf","raw_type":"text"},{"id":"pmh:oai:CiteSeerX.psu:10.1.1.680.1895","is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.680.1895","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://www.ifp.illinois.edu/%7Eangelia/CDCmyopic-learning-submit.pdf","raw_type":"text"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/10","display_name":"Reduced inequalities","score":0.4300000071525574}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":26,"referenced_works":["https://openalex.org/W1498395183","https://openalex.org/W1547358136","https://openalex.org/W1572167389","https://openalex.org/W1987832557","https://openalex.org/W2034586501","https://openalex.org/W2039661659","https://openalex.org/W2044212084","https://openalex.org/W2067831995","https://openalex.org/W2091087160","https://openalex.org/W2096605213","https://openalex.org/W2098865243","https://openalex.org/W2107396783","https://openalex.org/W2109469951","https://openalex.org/W2110152576","https://openalex.org/W2122489728","https://openalex.org/W2140950724","https://openalex.org/W2145574455","https://openalex.org/W2145976030","https://openalex.org/W2154834860","https://openalex.org/W2163220282","https://openalex.org/W2165744313","https://openalex.org/W2172813797","https://openalex.org/W3022273187","https://openalex.org/W3125863268","https://openalex.org/W3130117258","https://openalex.org/W6676561645"],"related_works":["https://openalex.org/W2961085424","https://openalex.org/W4306674287","https://openalex.org/W3046775127","https://openalex.org/W3107602296","https://openalex.org/W4394896187","https://openalex.org/W3170094116","https://openalex.org/W4386462264","https://openalex.org/W4364306694","https://openalex.org/W4312192474","https://openalex.org/W4283697347"],"abstract_inverted_index":{"We":[0,58,112,144],"study":[1],"the":[2,41,50,53,60,87,103,139,147,157,161,175,182,188,204,213,220],"problem":[3],"of":[4,11,27,43,63,65,81,142,150,156,219,222],"dynamic":[5],"learning":[6,45,67,223],"by":[7],"a":[8,16,25,78,217],"social":[9],"network":[10,35],"agents.":[12,111],"Each":[13],"agent":[14,73],"receives":[15,90],"signal":[17,85,226],"about":[18],"an":[19,209],"underlying":[20,54,158,162,189,214],"state":[21,55,163,190,215],"and":[22,86,102,212,225],"communicates":[23],"with":[24,166],"subset":[26],"agents":[28],"(his":[29],"neighbors)":[30],"in":[31,181],"each":[32,70,72],"period.":[33],"The":[34,93,125],"is":[36,56],"connected.":[37],"In":[38,185],"contrast":[39],"to":[40,96,106,130,133,153,169,199],"majority":[42],"existing":[44],"models,":[46],"we":[47,172],"focus":[48],"on":[49,203],"case":[51],"where":[52],"time-varying.":[57],"consider":[59],"following":[61],"class":[62,149],"rule":[64,224],"thumb":[66],"rules:":[68],"at":[69],"period,":[71],"constructs":[74],"his":[75,82,84],"posterior":[76],"as":[77,216],"weighted":[79],"average":[80],"prior,":[83],"information":[88],"he":[89],"from":[91],"neighbors.":[92],"weights":[94,104,128],"given":[95,105,129],"signals":[97,131],"can":[98,108],"vary":[99,109],"over":[100],"time":[101],"neighbors":[107],"across":[110],"distinguish":[113],"between":[114,208],"two":[115],"subclasses:":[116],"(1)":[117],"constant":[118,194],"weight":[119,123,177,195],"rules;":[120],"(2)":[121],"diminishing":[122,176],"rules.":[124],"latter":[126],"reduces":[127],"asymptotically":[132],"0.":[134],"Our":[135],"main":[136],"results":[137],"characterize":[138,200],"asymptotic":[140],"behavior":[141],"beliefs.":[143],"show":[145,173],"that":[146,174],"general":[148],"rules":[151,178,196],"leads":[152],"unbiased":[154],"estimates":[155],"state.":[159],"When":[160],"has":[164,191],"innovations":[165],"variance":[167],"tending":[168],"zero":[170],"asymptotically,":[171],"ensure":[179],"convergence":[180],"mean-square":[183],"sense.":[184],"contrast,":[186],"when":[187],"persistent":[192],"innovations,":[193],"enable":[197],"us":[198],"explicit":[201],"bounds":[202],"mean":[205],"square":[206],"error":[207],"agent\u2019s":[210],"belief":[211],"function":[218],"type":[221],"structure.":[227]},"counts_by_year":[{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":6},{"year":2021,"cited_by_count":2},{"year":2018,"cited_by_count":3},{"year":2017,"cited_by_count":3},{"year":2016,"cited_by_count":6},{"year":2015,"cited_by_count":3},{"year":2014,"cited_by_count":1},{"year":2013,"cited_by_count":4},{"year":2012,"cited_by_count":1}],"updated_date":"2026-04-04T16:13:02.066488","created_date":"2025-10-10T00:00:00"}
