{"id":"https://openalex.org/W4411471928","doi":"https://doi.org/10.1109/lcsys.2025.3581859","title":"Steering Large Agent Populations Using Mean-Field Schr\u00f6dinger Bridges With Gaussian Mixture Models","display_name":"Steering Large Agent Populations Using Mean-Field Schr\u00f6dinger Bridges With Gaussian Mixture Models","publication_year":2025,"publication_date":"2025-01-01","ids":{"openalex":"https://openalex.org/W4411471928","doi":"https://doi.org/10.1109/lcsys.2025.3581859"},"language":"en","primary_location":{"id":"doi:10.1109/lcsys.2025.3581859","is_oa":false,"landing_page_url":"https://doi.org/10.1109/lcsys.2025.3581859","pdf_url":null,"source":{"id":"https://openalex.org/S4306422535","display_name":"IEEE Control Systems Letters","issn_l":"2475-1456","issn":["2475-1456"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Control Systems Letters","raw_type":"journal-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/A5079918659","display_name":"George Rapakoulias","orcid":"https://orcid.org/0009-0000-8572-710X"},"institutions":[{"id":"https://openalex.org/I130701444","display_name":"Georgia Institute of Technology","ror":"https://ror.org/01zkghx44","country_code":"US","type":"education","lineage":["https://openalex.org/I130701444"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"George Rapakoulias","raw_affiliation_strings":["Department of Aerospace Engineering, Georgia Institute of Technology, Atlanta, GA, USA","Department of Aerospace Engineering of Georgia Institute of Technology, Georgia"],"affiliations":[{"raw_affiliation_string":"Department of Aerospace Engineering, Georgia Institute of Technology, Atlanta, GA, USA","institution_ids":["https://openalex.org/I130701444"]},{"raw_affiliation_string":"Department of Aerospace Engineering of Georgia Institute of Technology, Georgia","institution_ids":["https://openalex.org/I130701444"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5006117549","display_name":"Ali Reza Pedram","orcid":"https://orcid.org/0000-0003-4619-2231"},"institutions":[{"id":"https://openalex.org/I130701444","display_name":"Georgia Institute of Technology","ror":"https://ror.org/01zkghx44","country_code":"US","type":"education","lineage":["https://openalex.org/I130701444"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Ali Reza Pedram","raw_affiliation_strings":["Department of Aerospace Engineering, Georgia Institute of Technology, Atlanta, GA, USA","Department of Aerospace Engineering of Georgia Institute of Technology, Georgia"],"affiliations":[{"raw_affiliation_string":"Department of Aerospace Engineering, Georgia Institute of Technology, Atlanta, GA, USA","institution_ids":["https://openalex.org/I130701444"]},{"raw_affiliation_string":"Department of Aerospace Engineering of Georgia Institute of Technology, Georgia","institution_ids":["https://openalex.org/I130701444"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5077667229","display_name":"Panagiotis Tsiotras","orcid":"https://orcid.org/0000-0001-7563-4129"},"institutions":[{"id":"https://openalex.org/I130701444","display_name":"Georgia Institute of Technology","ror":"https://ror.org/01zkghx44","country_code":"US","type":"education","lineage":["https://openalex.org/I130701444"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Panagiotis Tsiotras","raw_affiliation_strings":["Department of Aerospace Engineering, Georgia Institute of Technology, Atlanta, GA, USA","Department of Aerospace Engineering of Georgia Institute of Technology, Georgia"],"affiliations":[{"raw_affiliation_string":"Department of Aerospace Engineering, Georgia Institute of Technology, Atlanta, GA, USA","institution_ids":["https://openalex.org/I130701444"]},{"raw_affiliation_string":"Department of Aerospace Engineering of Georgia Institute of Technology, Georgia","institution_ids":["https://openalex.org/I130701444"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5079918659"],"corresponding_institution_ids":["https://openalex.org/I130701444"],"apc_list":null,"apc_paid":null,"fwci":2.6577,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.89914866,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":99},"biblio":{"volume":"9","issue":null,"first_page":"1760","last_page":"1765"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12592","display_name":"Opinion Dynamics and Social Influence","score":0.9035000205039978,"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":0.9035000205039978,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/gaussian","display_name":"Gaussian","score":0.5512385368347168},{"id":"https://openalex.org/keywords/statistical-physics","display_name":"Statistical physics","score":0.496674120426178},{"id":"https://openalex.org/keywords/mean-field-theory","display_name":"Mean field theory","score":0.4920501112937927},{"id":"https://openalex.org/keywords/field","display_name":"Field (mathematics)","score":0.4183260500431061},{"id":"https://openalex.org/keywords/mixture-model","display_name":"Mixture model","score":0.41659265756607056},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.3728639483451843},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.3374350666999817},{"id":"https://openalex.org/keywords/physics","display_name":"Physics","score":0.33309000730514526},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.25958675146102905},{"id":"https://openalex.org/keywords/quantum-mechanics","display_name":"Quantum mechanics","score":0.13449490070343018},{"id":"https://openalex.org/keywords/pure-mathematics","display_name":"Pure mathematics","score":0.09590405225753784}],"concepts":[{"id":"https://openalex.org/C163716315","wikidata":"https://www.wikidata.org/wiki/Q901177","display_name":"Gaussian","level":2,"score":0.5512385368347168},{"id":"https://openalex.org/C121864883","wikidata":"https://www.wikidata.org/wiki/Q677916","display_name":"Statistical physics","level":1,"score":0.496674120426178},{"id":"https://openalex.org/C202213908","wikidata":"https://www.wikidata.org/wiki/Q626011","display_name":"Mean field theory","level":2,"score":0.4920501112937927},{"id":"https://openalex.org/C9652623","wikidata":"https://www.wikidata.org/wiki/Q190109","display_name":"Field (mathematics)","level":2,"score":0.4183260500431061},{"id":"https://openalex.org/C61224824","wikidata":"https://www.wikidata.org/wiki/Q2260434","display_name":"Mixture model","level":2,"score":0.41659265756607056},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.3728639483451843},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.3374350666999817},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.33309000730514526},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.25958675146102905},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.13449490070343018},{"id":"https://openalex.org/C202444582","wikidata":"https://www.wikidata.org/wiki/Q837863","display_name":"Pure mathematics","level":1,"score":0.09590405225753784}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/lcsys.2025.3581859","is_oa":false,"landing_page_url":"https://doi.org/10.1109/lcsys.2025.3581859","pdf_url":null,"source":{"id":"https://openalex.org/S4306422535","display_name":"IEEE Control Systems Letters","issn_l":"2475-1456","issn":["2475-1456"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Control Systems Letters","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":28,"referenced_works":["https://openalex.org/W1858982327","https://openalex.org/W2011000015","https://openalex.org/W2038686546","https://openalex.org/W2886722878","https://openalex.org/W2964229334","https://openalex.org/W2978236721","https://openalex.org/W3016115703","https://openalex.org/W3036842247","https://openalex.org/W3129947101","https://openalex.org/W3169939870","https://openalex.org/W3175899508","https://openalex.org/W3183269529","https://openalex.org/W3194468394","https://openalex.org/W4230008158","https://openalex.org/W4245164763","https://openalex.org/W4385403769","https://openalex.org/W4391022113","https://openalex.org/W4393861504","https://openalex.org/W4402264169","https://openalex.org/W4403052611","https://openalex.org/W4405786029","https://openalex.org/W4407951109","https://openalex.org/W4411471928","https://openalex.org/W6811167374","https://openalex.org/W6842519810","https://openalex.org/W6873728997","https://openalex.org/W6875144956","https://openalex.org/W6875218631"],"related_works":["https://openalex.org/W1975321310","https://openalex.org/W2014494654","https://openalex.org/W3130349901","https://openalex.org/W1579833936","https://openalex.org/W2107361128","https://openalex.org/W2095350775","https://openalex.org/W2990323019","https://openalex.org/W2014842417","https://openalex.org/W1578916557","https://openalex.org/W82723519"],"abstract_inverted_index":{"The":[0],"Mean-Field":[1],"Schr\u00f6dinger":[2],"Bridge":[3],"(MFSB)":[4],"problem":[5,9,67,147],"is":[6,39],"an":[7],"optimization":[8,93],"aiming":[10],"to":[11,18,29,40,115,155],"find":[12],"the":[13,32,37,42,55,79,117,121,149,152,156,159,163,167,171,179],"minimum":[14],"effort":[15],"control":[16,41],"policy":[17],"drive":[19],"a":[20,45,111,136,143,191],"McKean-Vlassov":[21],"stochastic":[22,92],"differential":[23],"equation":[24],"from":[25,148],"one":[26],"probability":[27,57],"measure":[28,58],"another.":[30],"In":[31],"context":[33],"of":[34,44,47,59,78,120,135,138,151,158,166,193],"multi-agent":[35],"control,":[36],"objective":[38],"configuration":[43],"swarm":[46],"identical,":[48],"interacting":[49],"cooperative":[50],"agents,":[51],"as":[52],"captured":[53],"by":[54],"time-varying":[56],"their":[60],"state.":[61],"Available":[62],"methods":[63],"for":[64,68,103],"solving":[65,142],"this":[66],"distributions":[69],"with":[70],"continuous":[71],"support":[72],"rely":[73],"either":[74],"on":[75,83,178,190],"spatial":[76],"discretizations":[77],"problem\u2019s":[80],"domain":[81],"or":[82],"approximating":[84],"optimal":[85,118],"solutions":[86,119],"using":[87],"neural":[88],"networks":[89],"trained":[90],"through":[91],"schemes.":[94],"For":[95],"agents":[96],"following":[97],"Linear":[98],"Time":[99],"Varying":[100],"dynamics,":[101],"and":[102],"Gaussian":[104],"Mixture":[105],"Model":[106],"boundary":[107],"distributions,":[108],"we":[109],"propose":[110],"highly":[112],"efficient":[113],"parameterization":[114],"approximate":[116],"corresponding":[122],"MFSB":[123],"in":[124],"closed":[125],"form,":[126],"without":[127],"any":[128],"learning":[129],"step.":[130],"Our":[131],"proposed":[132,172],"approach":[133,189],"consists":[134],"mixture":[137,154],"elementary":[139],"policies,":[140],"each":[141],"Gaussian-to-Gaussian":[144],"Covariance":[145,168],"Steering":[146,169],"components":[150,157],"initial":[153],"terminal":[160],"mixture.":[161],"Leveraging":[162],"semidefinite":[164],"formulation":[165],"problem,":[170],"solver":[173],"can":[174],"handle":[175],"probabilistic":[176],"constraints":[177],"system\u2019s":[180],"state":[181],"while":[182],"maintaining":[183],"numerical":[184,194],"tractability.":[185],"We":[186],"illustrate":[187],"our":[188],"variety":[192],"examples.":[195]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":1}],"updated_date":"2026-03-27T05:58:40.876381","created_date":"2025-10-10T00:00:00"}
