{"id":"https://openalex.org/W4405429255","doi":"https://doi.org/10.1109/lra.2024.3518304","title":"Learning Multi-Agent Coordination for Replenishment At Sea","display_name":"Learning Multi-Agent Coordination for Replenishment At Sea","publication_year":2024,"publication_date":"2024-12-16","ids":{"openalex":"https://openalex.org/W4405429255","doi":"https://doi.org/10.1109/lra.2024.3518304"},"language":"en","primary_location":{"id":"doi:10.1109/lra.2024.3518304","is_oa":false,"landing_page_url":"https://doi.org/10.1109/lra.2024.3518304","pdf_url":null,"source":{"id":"https://openalex.org/S4210169774","display_name":"IEEE Robotics and Automation Letters","issn_l":"2377-3766","issn":["2377-3766","2377-3774"],"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 Robotics and Automation 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/A5009175771","display_name":"Byeolyi Han","orcid":null},"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":"Byeolyi Han","raw_affiliation_strings":["Georgia Institute of Technology, Atlanta, GA, USA"],"raw_orcid":"https://orcid.org/0000-0001-6464-2457","affiliations":[{"raw_affiliation_string":"Georgia Institute of Technology, Atlanta, GA, USA","institution_ids":["https://openalex.org/I130701444"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Minwoo Cho","orcid":"https://orcid.org/0000-0003-2072-149X"},"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":"Minwoo Cho","raw_affiliation_strings":["Georgia Institute of Technology, Atlanta, GA, USA"],"raw_orcid":"https://orcid.org/0000-0003-2072-149X","affiliations":[{"raw_affiliation_string":"Georgia Institute of Technology, Atlanta, GA, USA","institution_ids":["https://openalex.org/I130701444"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5067804383","display_name":"Letian Chen","orcid":"https://orcid.org/0000-0001-9238-7342"},"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":"Letian Chen","raw_affiliation_strings":["Georgia Institute of Technology, Atlanta, GA, USA"],"raw_orcid":"https://orcid.org/0000-0001-9238-7342","affiliations":[{"raw_affiliation_string":"Georgia Institute of Technology, Atlanta, GA, USA","institution_ids":["https://openalex.org/I130701444"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5005412601","display_name":"Rohan Paleja","orcid":"https://orcid.org/0000-0002-0773-8054"},"institutions":[{"id":"https://openalex.org/I4210122954","display_name":"MIT Lincoln Laboratory","ror":"https://ror.org/022z6jk58","country_code":"US","type":"facility","lineage":["https://openalex.org/I4210122954","https://openalex.org/I63966007"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Rohan Paleja","raw_affiliation_strings":["MIT Lincoln Laboratory, Lexington, MA, USA"],"raw_orcid":"https://orcid.org/0000-0002-0773-8054","affiliations":[{"raw_affiliation_string":"MIT Lincoln Laboratory, Lexington, MA, USA","institution_ids":["https://openalex.org/I4210122954"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101572719","display_name":"Zixuan Wu","orcid":"https://orcid.org/0000-0002-8742-4986"},"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":"Zixuan Wu","raw_affiliation_strings":["Georgia Institute of Technology, Atlanta, GA, USA"],"raw_orcid":"https://orcid.org/0000-0002-8742-4986","affiliations":[{"raw_affiliation_string":"Georgia Institute of Technology, Atlanta, GA, USA","institution_ids":["https://openalex.org/I130701444"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5087591159","display_name":"Sean Ye","orcid":null},"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":"Sean Ye","raw_affiliation_strings":["Georgia Institute of Technology, Atlanta, GA, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Georgia Institute of Technology, Atlanta, GA, USA","institution_ids":["https://openalex.org/I130701444"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5008759602","display_name":"Esmaeil Seraj","orcid":"https://orcid.org/0000-0002-0147-1037"},"institutions":[{"id":"https://openalex.org/I1311688040","display_name":"Amazon (United States)","ror":"https://ror.org/04mv4n011","country_code":"US","type":"company","lineage":["https://openalex.org/I1311688040"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Esmaeil Seraj","raw_affiliation_strings":["Amazon Robotics, Seattle, WA, USA"],"raw_orcid":"https://orcid.org/0000-0002-0147-1037","affiliations":[{"raw_affiliation_string":"Amazon Robotics, Seattle, WA, USA","institution_ids":["https://openalex.org/I1311688040"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5032483735","display_name":"David Sidoti","orcid":"https://orcid.org/0000-0002-2347-225X"},"institutions":[{"id":"https://openalex.org/I1288214837","display_name":"United States Naval Research Laboratory","ror":"https://ror.org/04d23a975","country_code":"US","type":"facility","lineage":["https://openalex.org/I1288214837","https://openalex.org/I1330347796","https://openalex.org/I175003984","https://openalex.org/I3130687028"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"David Sidoti","raw_affiliation_strings":["US Naval Research Laboratory, Monterey, CA, USA"],"raw_orcid":"https://orcid.org/0000-0002-2347-225X","affiliations":[{"raw_affiliation_string":"US Naval Research Laboratory, Monterey, CA, USA","institution_ids":["https://openalex.org/I1288214837"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5008211323","display_name":"Matthew Gombolay","orcid":"https://orcid.org/0000-0002-5321-6038"},"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":"Matthew Gombolay","raw_affiliation_strings":["Georgia Institute of Technology, Atlanta, GA, USA"],"raw_orcid":"https://orcid.org/0000-0002-5321-6038","affiliations":[{"raw_affiliation_string":"Georgia Institute of Technology, Atlanta, GA, USA","institution_ids":["https://openalex.org/I130701444"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.28853727,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"10","issue":"2","first_page":"1018","last_page":"1025"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10551","display_name":"Scheduling and Optimization Algorithms","score":0.8690000176429749,"subfield":{"id":"https://openalex.org/subfields/2209","display_name":"Industrial and Manufacturing 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/T10551","display_name":"Scheduling and Optimization Algorithms","score":0.8690000176429749,"subfield":{"id":"https://openalex.org/subfields/2209","display_name":"Industrial and Manufacturing 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/T11814","display_name":"Advanced Manufacturing and Logistics Optimization","score":0.7455000281333923,"subfield":{"id":"https://openalex.org/subfields/2209","display_name":"Industrial and Manufacturing 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/T10456","display_name":"Multi-Agent Systems and Negotiation","score":0.7246000170707703,"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/computer-science","display_name":"Computer science","score":0.3448736071586609}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.3448736071586609}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/lra.2024.3518304","is_oa":false,"landing_page_url":"https://doi.org/10.1109/lra.2024.3518304","pdf_url":null,"source":{"id":"https://openalex.org/S4210169774","display_name":"IEEE Robotics and Automation Letters","issn_l":"2377-3766","issn":["2377-3766","2377-3774"],"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 Robotics and Automation Letters","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":33,"referenced_works":["https://openalex.org/W1591713425","https://openalex.org/W1972391046","https://openalex.org/W2176241949","https://openalex.org/W2790839280","https://openalex.org/W2798598284","https://openalex.org/W2889586143","https://openalex.org/W2903588686","https://openalex.org/W2911286998","https://openalex.org/W2963523627","https://openalex.org/W3092066952","https://openalex.org/W3167287256","https://openalex.org/W3185823870","https://openalex.org/W4212994175","https://openalex.org/W4306786778","https://openalex.org/W4385071479","https://openalex.org/W4385245566","https://openalex.org/W4386024630","https://openalex.org/W4393157058","https://openalex.org/W4400877128","https://openalex.org/W6713411898","https://openalex.org/W6738796088","https://openalex.org/W6757784512","https://openalex.org/W6758763022","https://openalex.org/W6760783655","https://openalex.org/W6766805167","https://openalex.org/W6780191816","https://openalex.org/W6781750019","https://openalex.org/W6784097869","https://openalex.org/W6796861069","https://openalex.org/W6802002411","https://openalex.org/W6840380725","https://openalex.org/W6845835355","https://openalex.org/W6860054160"],"related_works":["https://openalex.org/W4391375266","https://openalex.org/W2899084033","https://openalex.org/W2748952813","https://openalex.org/W2390279801","https://openalex.org/W4391913857","https://openalex.org/W2358668433","https://openalex.org/W4396701345","https://openalex.org/W2376932109","https://openalex.org/W2001405890","https://openalex.org/W4396696052"],"abstract_inverted_index":{"Optimizing":[0],"large-scale":[1],"logistics":[2,37,151],"is":[3],"computationally":[4],"challenging":[5],"due":[6],"to":[7,12,15,69,104,131,137,148],"its":[8],"scale":[9],"and":[10,17,64,99,108,125],"requirement":[11],"be":[13],"robust":[14],"stochastic":[16],"time-varying":[18],"weather":[19,42,74],"disturbances.":[20],"However,":[21],"prior":[22],"research":[23],"in":[24,145],"multi-agent":[25],"reinforcement":[26],"learning":[27],"(MARL)":[28],"does":[29],"not":[30],"address":[31,45],"scenarios":[32],"that":[33,92,118],"capture":[34],"complexity":[35],"of":[36,58,73,121],"operations":[38],"influenced":[39],"by":[40,112,135],"dynamic":[41],"patterns.":[43],"To":[44,82],"this":[46,83],"gap,":[47],"we":[48,85],"suggest":[49],"a":[50,88,94,142],"new":[51],"MARL":[52,90,147],"environment,$\\textsc":[53],"{Marine}$that":[54],"has":[55],"two":[56],"types":[57],"agents":[59],"equipped":[60],"with":[61],"limited":[62],"resources":[63],"integrates":[65],"real":[66],"wave":[67],"data":[68],"model":[70,130],"the":[71,76,119],"influences":[72],"on":[75],"replenishment":[77],"at":[78],"sea":[79],"(RAS)":[80],"operation.":[81],"end,":[84],"propose":[86],"SchedHGNN,":[87],"novel":[89],"algorithm":[91],"incorporates":[93],"heterogeneous":[95],"graph":[96],"neural":[97],"network":[98],"an":[100],"intrinsic":[101],"reward":[102],"scheme":[103],"enhance":[105],"agent":[106],"coordination":[107],"mitigate":[109],"challenges":[110],"induced":[111],"environment":[113],"non-stationarity.":[114],"Our":[115],"results":[116],"show":[117],"combination":[120],"effective":[122],"RAS":[123],"scheduling":[124],"improved":[126],"communication":[127],"enables":[128],"our":[129],"outperform":[132],"competitive":[133],"baselines":[134],"up":[136],"37.8%.":[138],"This":[139],"achievement":[140],"marks":[141],"significant":[143],"advancement":[144],"applying":[146],"complex,":[149],"real-world":[150],"scenarios.":[152]},"counts_by_year":[],"updated_date":"2026-07-29T09:40:50.615796","created_date":"2025-10-10T00:00:00"}
