{"id":"https://openalex.org/W7125364074","doi":"https://doi.org/10.48550/arxiv.2601.14275","title":"Quality or Quantity? Error-Informed Selective Online Learning with Gaussian Processes in Multi-Agent Systems: Extended Version","display_name":"Quality or Quantity? Error-Informed Selective Online Learning with Gaussian Processes in Multi-Agent Systems: Extended Version","publication_year":2026,"publication_date":"2026-01-10","ids":{"openalex":"https://openalex.org/W7125364074","doi":"https://doi.org/10.48550/arxiv.2601.14275"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2601.14275","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2601.14275","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"article"},"type":"preprint","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.48550/arxiv.2601.14275","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5070041954","display_name":"Zewen Yang","orcid":"https://orcid.org/0000-0001-9974-3231"},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Yang, Zewen","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5123576338","display_name":"Xiaobing Dai","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Dai, Xiaobing","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5123627392","display_name":"Jiajun Cheng","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Cheng, Jiajun","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5123553993","display_name":"Yulong Huang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Huang, Yulong","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5066086792","display_name":"Peng Shi","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Shi, Peng","raw_affiliation_strings":[],"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5070041954"],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12814","display_name":"Gaussian Processes and Bayesian Inference","score":0.953000009059906,"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"}},"topics":[{"id":"https://openalex.org/T12814","display_name":"Gaussian Processes and Bayesian Inference","score":0.953000009059906,"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/T12101","display_name":"Advanced Bandit Algorithms Research","score":0.01119999960064888,"subfield":{"id":"https://openalex.org/subfields/1803","display_name":"Management Science and Operations Research"},"field":{"id":"https://openalex.org/fields/18","display_name":"Decision Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T10848","display_name":"Advanced Multi-Objective Optimization Algorithms","score":0.003800000064074993,"subfield":{"id":"https://openalex.org/subfields/1703","display_name":"Computational Theory and Mathematics"},"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/gaussian-process","display_name":"Gaussian process","score":0.5823000073432922},{"id":"https://openalex.org/keywords/quality","display_name":"Quality (philosophy)","score":0.5557000041007996},{"id":"https://openalex.org/keywords/online-learning","display_name":"Online learning","score":0.445499986410141},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.444599986076355},{"id":"https://openalex.org/keywords/function","display_name":"Function (biology)","score":0.4124000072479248},{"id":"https://openalex.org/keywords/selection","display_name":"Selection (genetic algorithm)","score":0.3831000030040741},{"id":"https://openalex.org/keywords/greedy-algorithm","display_name":"Greedy algorithm","score":0.3596999943256378},{"id":"https://openalex.org/keywords/online-machine-learning","display_name":"Online machine learning","score":0.3573000133037567},{"id":"https://openalex.org/keywords/term","display_name":"Term (time)","score":0.35120001435279846}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7430999875068665},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6409000158309937},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.6388999819755554},{"id":"https://openalex.org/C61326573","wikidata":"https://www.wikidata.org/wiki/Q1496376","display_name":"Gaussian process","level":3,"score":0.5823000073432922},{"id":"https://openalex.org/C2779530757","wikidata":"https://www.wikidata.org/wiki/Q1207505","display_name":"Quality (philosophy)","level":2,"score":0.5557000041007996},{"id":"https://openalex.org/C2986087404","wikidata":"https://www.wikidata.org/wiki/Q15946010","display_name":"Online learning","level":2,"score":0.445499986410141},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.444599986076355},{"id":"https://openalex.org/C14036430","wikidata":"https://www.wikidata.org/wiki/Q3736076","display_name":"Function (biology)","level":2,"score":0.4124000072479248},{"id":"https://openalex.org/C81917197","wikidata":"https://www.wikidata.org/wiki/Q628760","display_name":"Selection (genetic algorithm)","level":2,"score":0.3831000030040741},{"id":"https://openalex.org/C51823790","wikidata":"https://www.wikidata.org/wiki/Q504353","display_name":"Greedy algorithm","level":2,"score":0.3596999943256378},{"id":"https://openalex.org/C115903097","wikidata":"https://www.wikidata.org/wiki/Q7094097","display_name":"Online machine learning","level":3,"score":0.3573000133037567},{"id":"https://openalex.org/C61797465","wikidata":"https://www.wikidata.org/wiki/Q1188986","display_name":"Term (time)","level":2,"score":0.35120001435279846},{"id":"https://openalex.org/C163716315","wikidata":"https://www.wikidata.org/wiki/Q901177","display_name":"Gaussian","level":2,"score":0.3499000072479248},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.31310001015663147},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.311599999666214},{"id":"https://openalex.org/C59656382","wikidata":"https://www.wikidata.org/wiki/Q191536","display_name":"Conjunction (astronomy)","level":2,"score":0.3109999895095825},{"id":"https://openalex.org/C196921405","wikidata":"https://www.wikidata.org/wiki/Q786431","display_name":"Online algorithm","level":2,"score":0.2815999984741211},{"id":"https://openalex.org/C2982736386","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Statistical learning","level":2,"score":0.2766000032424927},{"id":"https://openalex.org/C77967617","wikidata":"https://www.wikidata.org/wiki/Q4677561","display_name":"Active learning (machine learning)","level":2,"score":0.2728999853134155},{"id":"https://openalex.org/C2777851325","wikidata":"https://www.wikidata.org/wiki/Q7094102","display_name":"Online model","level":2,"score":0.27239999175071716},{"id":"https://openalex.org/C125014702","wikidata":"https://www.wikidata.org/wiki/Q4680749","display_name":"Adaptive learning","level":2,"score":0.2624000012874603},{"id":"https://openalex.org/C18555067","wikidata":"https://www.wikidata.org/wiki/Q8375051","display_name":"Joint (building)","level":2,"score":0.2623000144958496},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.2614000141620636},{"id":"https://openalex.org/C148220186","wikidata":"https://www.wikidata.org/wiki/Q7111912","display_name":"Outcome (game theory)","level":2,"score":0.2563999891281128},{"id":"https://openalex.org/C22367795","wikidata":"https://www.wikidata.org/wiki/Q7625208","display_name":"Structured prediction","level":2,"score":0.25279998779296875},{"id":"https://openalex.org/C179799912","wikidata":"https://www.wikidata.org/wiki/Q205084","display_name":"Computational complexity theory","level":2,"score":0.2513999938964844},{"id":"https://openalex.org/C2779582901","wikidata":"https://www.wikidata.org/wiki/Q21013010","display_name":"Distributed learning","level":2,"score":0.25060001015663147}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2601.14275","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2601.14275","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"article"}],"best_oa_location":{"id":"doi:10.48550/arxiv.2601.14275","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2601.14275","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"article"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/10","score":0.7792709469795227,"display_name":"Reduced inequalities"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Effective":[0],"cooperation":[1],"is":[2,23],"pivotal":[3],"in":[4,49,133],"distributed":[5,62,68,169],"learning":[6,21,59,149],"for":[7,38,61,110,118,125],"multi-agent":[8],"systems,":[9],"where":[10],"the":[11,14,19,28,42,55,82,88,103,136,157,160,167],"interplay":[12],"between":[13],"quantity":[15,48],"and":[16,113,128,141],"quality":[17,46,90],"of":[18,30,33,159],"machine":[20],"models":[22,35,92],"crucial.":[24],"This":[25],"paper":[26],"reveals":[27],"irrationality":[29],"indiscriminate":[31],"inclusion":[32],"all":[34],"on":[36],"agents":[37],"joint":[39],"prediction,":[40],"highlighting":[41],"imperative":[43],"to":[44,76,86,146,155],"prioritize":[45],"over":[47,166],"cooperative":[50],"learning.":[51],"Specifically,":[52],"we":[53],"present":[54],"first":[56],"selective":[57],"online":[58],"framework":[60],"Gaussian":[63],"process":[64],"(GP)":[65],"regression,":[66],"namely":[67],"error-informed":[69,137],"GP":[70,91,170],"(EIGP),":[71],"that":[72],"enables":[73],"each":[74],"agent":[75],"assess":[77],"its":[78,164],"neighboring":[79],"collaborators,":[80],"using":[81],"proposed":[83],"selection":[84],"function":[85],"choose":[87],"higher":[89],"with":[93,135,172],"less":[94],"prediction":[95,112,120,127],"errors.":[96],"Moreover,":[97],"algorithmic":[98],"enhancements":[99],"are":[100,131,153],"embedded":[101],"within":[102],"EIGP,":[104],"including":[105],"a":[106,142],"greedy":[107],"algorithm":[108,116],"(gEIGP)":[109],"accelerating":[111],"an":[114],"adaptive":[115],"(aEIGP)":[117],"improving":[119],"accuracy.":[121],"In":[122],"addition,":[123],"approaches":[124],"fast":[126],"model":[129],"update":[130],"introduced":[132],"conjunction":[134],"quantification":[138],"term":[139],"iteration":[140],"data":[143],"deletion":[144],"strategy":[145],"achieve":[147],"real-time":[148],"operations.":[150],"Numerical":[151],"simulations":[152],"performed":[154],"demonstrate":[156],"effectiveness":[158],"developed":[161],"methodology,":[162],"showcasing":[163],"superiority":[165],"state-of-the-art":[168],"methods":[171],"different":[173],"benchmarks.":[174]},"counts_by_year":[],"updated_date":"2026-01-23T23:24:52.574035","created_date":"2026-01-23T00:00:00"}
