{"id":"https://openalex.org/W4312948503","doi":"https://doi.org/10.1109/tetci.2022.3221483","title":"Variational Reinforcement Learning for Hyper-Parameter Tuning of Adaptive Evolutionary Algorithm","display_name":"Variational Reinforcement Learning for Hyper-Parameter Tuning of Adaptive Evolutionary Algorithm","publication_year":2022,"publication_date":"2022-11-18","ids":{"openalex":"https://openalex.org/W4312948503","doi":"https://doi.org/10.1109/tetci.2022.3221483"},"language":"en","primary_location":{"id":"doi:10.1109/tetci.2022.3221483","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tetci.2022.3221483","pdf_url":null,"source":{"id":"https://openalex.org/S4210210251","display_name":"IEEE Transactions on Emerging Topics in Computational Intelligence","issn_l":"2471-285X","issn":["2471-285X"],"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 Transactions on Emerging Topics in Computational Intelligence","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/A5060123829","display_name":"Haotian Zhang","orcid":null},"institutions":[{"id":"https://openalex.org/I87445476","display_name":"Xi'an Jiaotong University","ror":"https://ror.org/017zhmm22","country_code":"CN","type":"education","lineage":["https://openalex.org/I87445476"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Haotian Zhang","raw_affiliation_strings":["School of Mathematics and Statistics and National Engineering Laboratory for Big Data Analytics, Xi&#x0027;an Jiaotong University, Xi&#x0027;an, China"],"affiliations":[{"raw_affiliation_string":"School of Mathematics and Statistics and National Engineering Laboratory for Big Data Analytics, Xi&#x0027;an Jiaotong University, Xi&#x0027;an, China","institution_ids":["https://openalex.org/I87445476"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5005474942","display_name":"Jianyong Sun","orcid":"https://orcid.org/0000-0002-9188-1856"},"institutions":[{"id":"https://openalex.org/I87445476","display_name":"Xi'an Jiaotong University","ror":"https://ror.org/017zhmm22","country_code":"CN","type":"education","lineage":["https://openalex.org/I87445476"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jianyong Sun","raw_affiliation_strings":["School of Mathematics and Statistics and National Engineering Laboratory for Big Data Analytics, Xi&#x0027;an Jiaotong University, Xi&#x0027;an, China"],"affiliations":[{"raw_affiliation_string":"School of Mathematics and Statistics and National Engineering Laboratory for Big Data Analytics, Xi&#x0027;an Jiaotong University, Xi&#x0027;an, China","institution_ids":["https://openalex.org/I87445476"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5043861652","display_name":"Yuhao Wang","orcid":"https://orcid.org/0000-0002-6051-8659"},"institutions":[{"id":"https://openalex.org/I168719708","display_name":"City University of Hong Kong","ror":"https://ror.org/03q8dnn23","country_code":"HK","type":"education","lineage":["https://openalex.org/I168719708"]}],"countries":["HK"],"is_corresponding":false,"raw_author_name":"Yuhao Wang","raw_affiliation_strings":["School of Data Science, City University of Hong Kong, Hong Kong, Hong Kong"],"affiliations":[{"raw_affiliation_string":"School of Data Science, City University of Hong Kong, Hong Kong, Hong Kong","institution_ids":["https://openalex.org/I168719708"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5057345644","display_name":"Jialong Shi","orcid":"https://orcid.org/0000-0002-4965-916X"},"institutions":[{"id":"https://openalex.org/I87445476","display_name":"Xi'an Jiaotong University","ror":"https://ror.org/017zhmm22","country_code":"CN","type":"education","lineage":["https://openalex.org/I87445476"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jialong Shi","raw_affiliation_strings":["School of Mathematics and Statistics and National Engineering Laboratory for Big Data Analytics, Xi&#x0027;an Jiaotong University, Xi&#x0027;an, China"],"affiliations":[{"raw_affiliation_string":"School of Mathematics and Statistics and National Engineering Laboratory for Big Data Analytics, Xi&#x0027;an Jiaotong University, Xi&#x0027;an, China","institution_ids":["https://openalex.org/I87445476"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5109280540","display_name":"Zongben Xu","orcid":"https://orcid.org/0000-0002-4066-2338"},"institutions":[{"id":"https://openalex.org/I87445476","display_name":"Xi'an Jiaotong University","ror":"https://ror.org/017zhmm22","country_code":"CN","type":"education","lineage":["https://openalex.org/I87445476"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zongben Xu","raw_affiliation_strings":["School of Mathematics and Statistics and National Engineering Laboratory for Big Data Analytics, Xi&#x0027;an Jiaotong University, Xi&#x0027;an, China"],"affiliations":[{"raw_affiliation_string":"School of Mathematics and Statistics and National Engineering Laboratory for Big Data Analytics, Xi&#x0027;an Jiaotong University, Xi&#x0027;an, China","institution_ids":["https://openalex.org/I87445476"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5060123829"],"corresponding_institution_ids":["https://openalex.org/I87445476"],"apc_list":null,"apc_paid":null,"fwci":1.6548,"has_fulltext":false,"cited_by_count":12,"citation_normalized_percentile":{"value":0.86633866,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":99},"biblio":{"volume":"7","issue":"5","first_page":"1511","last_page":"1526"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10100","display_name":"Metaheuristic Optimization Algorithms Research","score":0.9990000128746033,"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/T10100","display_name":"Metaheuristic Optimization Algorithms Research","score":0.9990000128746033,"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/T11975","display_name":"Evolutionary Algorithms and Applications","score":0.9987000226974487,"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/T10848","display_name":"Advanced Multi-Objective Optimization Algorithms","score":0.9962000250816345,"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/algorithm","display_name":"Algorithm","score":0.6019167304039001},{"id":"https://openalex.org/keywords/reinforcement-learning","display_name":"Reinforcement learning","score":0.5476294755935669},{"id":"https://openalex.org/keywords/notation","display_name":"Notation","score":0.5180587768554688},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.4977135956287384},{"id":"https://openalex.org/keywords/crossover","display_name":"Crossover","score":0.4614912271499634},{"id":"https://openalex.org/keywords/distribution","display_name":"Distribution (mathematics)","score":0.42761939764022827},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.38840189576148987},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.36254748702049255},{"id":"https://openalex.org/keywords/mathematical-analysis","display_name":"Mathematical analysis","score":0.11579254269599915},{"id":"https://openalex.org/keywords/arithmetic","display_name":"Arithmetic","score":0.09789034724235535}],"concepts":[{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.6019167304039001},{"id":"https://openalex.org/C97541855","wikidata":"https://www.wikidata.org/wiki/Q830687","display_name":"Reinforcement learning","level":2,"score":0.5476294755935669},{"id":"https://openalex.org/C45357846","wikidata":"https://www.wikidata.org/wiki/Q2001982","display_name":"Notation","level":2,"score":0.5180587768554688},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.4977135956287384},{"id":"https://openalex.org/C122507166","wikidata":"https://www.wikidata.org/wiki/Q628906","display_name":"Crossover","level":2,"score":0.4614912271499634},{"id":"https://openalex.org/C110121322","wikidata":"https://www.wikidata.org/wiki/Q865811","display_name":"Distribution (mathematics)","level":2,"score":0.42761939764022827},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.38840189576148987},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.36254748702049255},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.11579254269599915},{"id":"https://openalex.org/C94375191","wikidata":"https://www.wikidata.org/wiki/Q11205","display_name":"Arithmetic","level":1,"score":0.09789034724235535}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tetci.2022.3221483","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tetci.2022.3221483","pdf_url":null,"source":{"id":"https://openalex.org/S4210210251","display_name":"IEEE Transactions on Emerging Topics in Computational Intelligence","issn_l":"2471-285X","issn":["2471-285X"],"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 Transactions on Emerging Topics in Computational Intelligence","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G1636070402","display_name":null,"funder_award_id":"11991023","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G2575459305","display_name":null,"funder_award_id":"61903294","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G7295677115","display_name":null,"funder_award_id":"62076197","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":56,"referenced_works":["https://openalex.org/W60686164","https://openalex.org/W1519597478","https://openalex.org/W1699954493","https://openalex.org/W1977026564","https://openalex.org/W2009086942","https://openalex.org/W2010861271","https://openalex.org/W2042253843","https://openalex.org/W2047229728","https://openalex.org/W2052367557","https://openalex.org/W2099655666","https://openalex.org/W2105658140","https://openalex.org/W2123066915","https://openalex.org/W2134154181","https://openalex.org/W2137340504","https://openalex.org/W2143983955","https://openalex.org/W2155007355","https://openalex.org/W2155529731","https://openalex.org/W2156194072","https://openalex.org/W2162145193","https://openalex.org/W2200000192","https://openalex.org/W2257979135","https://openalex.org/W2334782222","https://openalex.org/W2507221917","https://openalex.org/W2557488584","https://openalex.org/W2558097110","https://openalex.org/W2604763608","https://openalex.org/W2753160622","https://openalex.org/W2889965839","https://openalex.org/W2891186800","https://openalex.org/W2902454235","https://openalex.org/W2903569983","https://openalex.org/W2914049157","https://openalex.org/W2950680102","https://openalex.org/W2961614712","https://openalex.org/W2963775850","https://openalex.org/W2963862287","https://openalex.org/W2968187932","https://openalex.org/W3009407436","https://openalex.org/W3083439876","https://openalex.org/W4214717370","https://openalex.org/W4294646197","https://openalex.org/W4298857966","https://openalex.org/W4324317500","https://openalex.org/W4391602018","https://openalex.org/W6631259609","https://openalex.org/W6637967152","https://openalex.org/W6640963894","https://openalex.org/W6674686537","https://openalex.org/W6676203565","https://openalex.org/W6682849425","https://openalex.org/W6717367658","https://openalex.org/W6736057607","https://openalex.org/W6743661861","https://openalex.org/W6750254146","https://openalex.org/W6753146606","https://openalex.org/W6754038005"],"related_works":["https://openalex.org/W2347477706","https://openalex.org/W4299389082","https://openalex.org/W1943663474","https://openalex.org/W2306830238","https://openalex.org/W2110294633","https://openalex.org/W1978349322","https://openalex.org/W2630967916","https://openalex.org/W2102514425","https://openalex.org/W2392589811","https://openalex.org/W2969059916"],"abstract_inverted_index":{"The":[0,56],"performance":[1,215],"of":[2,38,81,100,117,120,143,169],"an":[3,148],"evolutionary":[4],"algorithm":[5,88,93],"(EA)":[6],"is":[7,42,51,61,105],"deeply":[8],"affected":[9],"by":[10,227],"its":[11],"control":[12,26,40],"parameter's":[13],"setting.":[14],"It":[15],"has":[16],"become":[17],"a":[18,29,73,90,187],"trend":[19],"in":[20,83],"recent":[21],"studies":[22],"to":[23,64,77,113,156,161,186],"treat":[24],"the":[25,35,39,54,65,79,85,98,101,115,118,125,158,167,181,195,203,208],"parameter":[27,41,49,58,127,221],"as":[28],"random":[30],"variable.":[31],"In":[32,68,152],"these":[33],"studies,":[34],"associated":[36],"distribution":[37],"updated":[43],"at":[44],"each":[45],"generation":[46],"and":[47,89,134,147,174,207,223,235],"new":[48,188],"setting":[50],"sampled":[52],"from":[53],"distribution.":[55],"distribution's":[57],"(called":[59],"hyper-parameter)":[60],"thus":[62],"critical":[63],"algorithmic":[66],"performance.":[67],"this":[69],"paper,":[70],"we":[71,110,154],"propose":[72,155],"variational":[74],"learning":[75,92],"framework":[76],"tune":[78,114],"hyper-parameters":[80,116,168],"EA,":[82],"which":[84,104],"expectation-maximization":[86],"(EM)":[87],"reinforcement":[91],"are":[94],"combined.":[95],"To":[96],"verify":[97],"effectiveness":[99],"proposed":[102],"method":[103],"named":[106],"Reinforcement":[107],"EM":[108],"(REM),":[109],"apply":[111],"it":[112],"distributions":[119,165],"two":[121],"important":[122],"parameters,":[123],"i.e.":[124],"scaling":[126],"(":[128,137],"<inline-formula":[129,138,170,175],"xmlns:mml=\"http://www.w3.org/1998/Math/MathML\"":[130,139,171,176],"xmlns:xlink=\"http://www.w3.org/1999/xlink\"><tex-math":[131,140,172,177],"notation=\"LaTeX\">$F$</tex-math></inline-formula>":[132,173],")":[133],"crossover":[135],"rate":[136],"notation=\"LaTeX\">$CR$</tex-math></inline-formula>":[141,178],"),":[142],"differential":[144],"evolution":[145],"(DE)":[146],"adaptive":[149,209],"DE":[150,206,210],"algorithm.":[151,238],"addition,":[153],"use":[157],"meta-learning":[159],"technique":[160],"learn":[162],"good":[163],"initial":[164],"for":[166],"so":[179],"that":[180,201],"REM":[182],"can":[183,211],"effectively":[184],"adapt":[185],"optimization":[189,237],"problem.":[190],"Experimental":[191],"results":[192],"obtained":[193],"on":[194],"CEC":[196],"2018":[197],"test":[198],"suite":[199],"show":[200],"with":[202,219,224],"tuned":[204,226],"hyper-parameters,":[205],"achieve":[212],"significantly":[213],"better":[214],"than":[216],"their":[217],"counterparts":[218],"empirical":[220],"settings":[222],"parameters":[225],"some":[228],"widely-used":[229],"tuning":[230],"methods,":[231],"including":[232],"ParamILS,":[233],"F-Race":[234],"Bayesian":[236]},"counts_by_year":[{"year":2025,"cited_by_count":6},{"year":2024,"cited_by_count":4},{"year":2023,"cited_by_count":2}],"updated_date":"2026-03-27T05:58:40.876381","created_date":"2025-10-10T00:00:00"}
