{"id":"https://openalex.org/W4286285540","doi":"https://doi.org/10.1109/iv51971.2022.9827289","title":"Social Learning In Markov Games: Empowering Autonomous Driving","display_name":"Social Learning In Markov Games: Empowering Autonomous Driving","publication_year":2022,"publication_date":"2022-06-05","ids":{"openalex":"https://openalex.org/W4286285540","doi":"https://doi.org/10.1109/iv51971.2022.9827289"},"language":"en","primary_location":{"id":"doi:10.1109/iv51971.2022.9827289","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iv51971.2022.9827289","pdf_url":null,"source":{"id":"https://openalex.org/S4363605370","display_name":"2022 IEEE Intelligent Vehicles Symposium (IV)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2022 IEEE Intelligent Vehicles Symposium (IV)","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/A5100385692","display_name":"Xu Chen","orcid":"https://orcid.org/0000-0001-9943-6020"},"institutions":[{"id":"https://openalex.org/I78577930","display_name":"Columbia University","ror":"https://ror.org/00hj8s172","country_code":"US","type":"education","lineage":["https://openalex.org/I78577930"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Xu Chen","raw_affiliation_strings":["Columbia University,Department of Civil Engineering and Engineering Mechanics,New York,NY,USA,10027"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Columbia University,Department of Civil Engineering and Engineering Mechanics,New York,NY,USA,10027","institution_ids":["https://openalex.org/I78577930"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5059724576","display_name":"Zechu Li","orcid":"https://orcid.org/0009-0002-1534-1740"},"institutions":[{"id":"https://openalex.org/I78577930","display_name":"Columbia University","ror":"https://ror.org/00hj8s172","country_code":"US","type":"education","lineage":["https://openalex.org/I78577930"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Zechu Li","raw_affiliation_strings":["Columbia University,Department of Computer Science,New York City,NY,USA,10027"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Columbia University,Department of Computer Science,New York City,NY,USA,10027","institution_ids":["https://openalex.org/I78577930"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5049787333","display_name":"Xuan Di","orcid":"https://orcid.org/0000-0003-2925-7697"},"institutions":[{"id":"https://openalex.org/I78577930","display_name":"Columbia University","ror":"https://ror.org/00hj8s172","country_code":"US","type":"education","lineage":["https://openalex.org/I78577930"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Xuan Di","raw_affiliation_strings":["Columbia University,Department of Civil Engineering and Engineering Mechanics,New York,NY,USA,10027","Data Science Institute, Columbia University, New York, NY, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Columbia University,Department of Civil Engineering and Engineering Mechanics,New York,NY,USA,10027","institution_ids":["https://openalex.org/I78577930"]},{"raw_affiliation_string":"Data Science Institute, Columbia University, New York, NY, USA","institution_ids":["https://openalex.org/I78577930"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":2.1045,"has_fulltext":false,"cited_by_count":7,"citation_normalized_percentile":{"value":0.88216945,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":98},"biblio":{"volume":null,"issue":null,"first_page":"478","last_page":"483"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10524","display_name":"Traffic control and management","score":0.9979000091552734,"subfield":{"id":"https://openalex.org/subfields/2207","display_name":"Control and Systems Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T10524","display_name":"Traffic control and management","score":0.9979000091552734,"subfield":{"id":"https://openalex.org/subfields/2207","display_name":"Control and Systems Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10462","display_name":"Reinforcement Learning in Robotics","score":0.994700014591217,"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"}},{"id":"https://openalex.org/T11099","display_name":"Autonomous Vehicle Technology and Safety","score":0.9908999800682068,"subfield":{"id":"https://openalex.org/subfields/2203","display_name":"Automotive Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/reinforcement-learning","display_name":"Reinforcement learning","score":0.7175499200820923},{"id":"https://openalex.org/keywords/leverage","display_name":"Leverage (statistics)","score":0.7043780088424683},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.69474858045578},{"id":"https://openalex.org/keywords/scheme","display_name":"Scheme (mathematics)","score":0.6830289363861084},{"id":"https://openalex.org/keywords/platoon","display_name":"Platoon","score":0.6254472732543945},{"id":"https://openalex.org/keywords/crash","display_name":"Crash","score":0.6033858060836792},{"id":"https://openalex.org/keywords/intersection","display_name":"Intersection (aeronautics)","score":0.5987672805786133},{"id":"https://openalex.org/keywords/markov-chain","display_name":"Markov chain","score":0.5645394921302795},{"id":"https://openalex.org/keywords/social-learning","display_name":"Social learning","score":0.5106974244117737},{"id":"https://openalex.org/keywords/q-learning","display_name":"Q-learning","score":0.4758341312408447},{"id":"https://openalex.org/keywords/markov-process","display_name":"Markov process","score":0.4147912263870239},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.31846511363983154},{"id":"https://openalex.org/keywords/transport-engineering","display_name":"Transport engineering","score":0.21715444326400757},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.20848912000656128},{"id":"https://openalex.org/keywords/control","display_name":"Control (management)","score":0.16452476382255554},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.14576062560081482},{"id":"https://openalex.org/keywords/knowledge-management","display_name":"Knowledge management","score":0.11056637763977051}],"concepts":[{"id":"https://openalex.org/C97541855","wikidata":"https://www.wikidata.org/wiki/Q830687","display_name":"Reinforcement learning","level":2,"score":0.7175499200820923},{"id":"https://openalex.org/C153083717","wikidata":"https://www.wikidata.org/wiki/Q6535263","display_name":"Leverage (statistics)","level":2,"score":0.7043780088424683},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.69474858045578},{"id":"https://openalex.org/C77618280","wikidata":"https://www.wikidata.org/wiki/Q1155772","display_name":"Scheme (mathematics)","level":2,"score":0.6830289363861084},{"id":"https://openalex.org/C2777735972","wikidata":"https://www.wikidata.org/wiki/Q1061967","display_name":"Platoon","level":3,"score":0.6254472732543945},{"id":"https://openalex.org/C183469790","wikidata":"https://www.wikidata.org/wiki/Q333501","display_name":"Crash","level":2,"score":0.6033858060836792},{"id":"https://openalex.org/C64543145","wikidata":"https://www.wikidata.org/wiki/Q162942","display_name":"Intersection (aeronautics)","level":2,"score":0.5987672805786133},{"id":"https://openalex.org/C98763669","wikidata":"https://www.wikidata.org/wiki/Q176645","display_name":"Markov chain","level":2,"score":0.5645394921302795},{"id":"https://openalex.org/C79416737","wikidata":"https://www.wikidata.org/wiki/Q2305519","display_name":"Social learning","level":2,"score":0.5106974244117737},{"id":"https://openalex.org/C188116033","wikidata":"https://www.wikidata.org/wiki/Q2664563","display_name":"Q-learning","level":3,"score":0.4758341312408447},{"id":"https://openalex.org/C159886148","wikidata":"https://www.wikidata.org/wiki/Q176645","display_name":"Markov process","level":2,"score":0.4147912263870239},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.31846511363983154},{"id":"https://openalex.org/C22212356","wikidata":"https://www.wikidata.org/wiki/Q775325","display_name":"Transport engineering","level":1,"score":0.21715444326400757},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.20848912000656128},{"id":"https://openalex.org/C2775924081","wikidata":"https://www.wikidata.org/wiki/Q55608371","display_name":"Control (management)","level":2,"score":0.16452476382255554},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.14576062560081482},{"id":"https://openalex.org/C56739046","wikidata":"https://www.wikidata.org/wiki/Q192060","display_name":"Knowledge management","level":1,"score":0.11056637763977051},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.0},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/iv51971.2022.9827289","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iv51971.2022.9827289","pdf_url":null,"source":{"id":"https://openalex.org/S4363605370","display_name":"2022 IEEE Intelligent Vehicles Symposium (IV)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2022 IEEE Intelligent Vehicles Symposium (IV)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":21,"referenced_works":["https://openalex.org/W361876","https://openalex.org/W92376239","https://openalex.org/W112918015","https://openalex.org/W1972177335","https://openalex.org/W1973039793","https://openalex.org/W1994883697","https://openalex.org/W2145339207","https://openalex.org/W2172193467","https://openalex.org/W2736601468","https://openalex.org/W2923669867","https://openalex.org/W2959402823","https://openalex.org/W2964164283","https://openalex.org/W3127561923","https://openalex.org/W3138181334","https://openalex.org/W3174021701","https://openalex.org/W6600018571","https://openalex.org/W6603783113","https://openalex.org/W6604633475","https://openalex.org/W6685285391","https://openalex.org/W6741002519","https://openalex.org/W6773319185"],"related_works":["https://openalex.org/W4286572054","https://openalex.org/W2555207388","https://openalex.org/W3171462553","https://openalex.org/W2983996496","https://openalex.org/W3189590538","https://openalex.org/W4389240635","https://openalex.org/W2461853023","https://openalex.org/W2136133395","https://openalex.org/W2935722734","https://openalex.org/W3102129050"],"abstract_inverted_index":{"In":[0,42,137],"a":[1,5,21,24,82,107],"multi-agent":[2],"system":[3],"(MAS),":[4],"social":[6,48,69,95,100,135,159],"learning":[7,49,58,96],"scheme":[8,25,50],"allows":[9],"independent":[10],"agents":[11,17],"to":[12,32,51,60,93,113,125,133,143,157],"learn":[13,65],"through":[14],"interactions":[15],"with":[16,86],"randomly":[18],"selected":[19],"from":[20],"pool.":[22],"Such":[23],"is":[26,91],"important":[27],"for":[28],"autonomous":[29],"vehicles":[30],"(AV)":[31],"navigate":[33],"complex":[34],"traffic":[35,72,80,114],"environments":[36],"consisting":[37],"of":[38],"many":[39],"road":[40],"users.":[41],"this":[43],"paper,":[44],"we":[45,105],"apply":[46,111],"the":[47,94],"Markov":[52],"games":[53],"and":[54,67,88,110,118],"leverage":[55],"deep":[56],"reinforcement":[57],"(DRL)":[59],"investigate":[61],"how":[62],"individual":[63],"AVs":[64,90,129,140,155],"policies":[66],"form":[68],"norms":[70,101],"in":[71],"scenarios.":[73],"To":[74,98],"capture":[75],"agents\u2019":[76],"different":[77],"attitudes":[78],"toward":[79],"environments,":[81],"heterogeneous":[83],"agent":[84],"pool":[85],"cooperative":[87,128,139],"defective":[89,126],"introduced":[92],"scheme.":[97],"solve":[99],"formed":[102],"by":[103],"AVs,":[104,127],"propose":[106],"DRL":[108],"algorithm,":[109],"them":[112],"scenarios:":[115],"unsignalized":[116],"intersection":[117],"highway":[119],"platoon.":[120],"We":[121,147],"find":[122,149],"that":[123,150],"compared":[124],"can":[130,153],"easily":[131],"conform":[132,156],"expected":[134,158],"norms.":[136,160],"addition,":[138],"would":[141],"lead":[142],"lower":[144],"crash":[145],"rates.":[146],"also":[148],"prioritized":[151],"roads/lanes":[152],"make":[154]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":2}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}
