{"id":"https://openalex.org/W3083489330","doi":"https://doi.org/10.1109/cec48606.2020.9185844","title":"Q-Learning Induced Artificial Bee Colony for Noisy Optimization","display_name":"Q-Learning Induced Artificial Bee Colony for Noisy Optimization","publication_year":2020,"publication_date":"2020-07-01","ids":{"openalex":"https://openalex.org/W3083489330","doi":"https://doi.org/10.1109/cec48606.2020.9185844","mag":"3083489330"},"language":"en","primary_location":{"id":"doi:10.1109/cec48606.2020.9185844","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cec48606.2020.9185844","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 IEEE Congress on Evolutionary Computation (CEC)","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/A5102829523","display_name":"Pratyusha Rakshit","orcid":"https://orcid.org/0000-0001-7350-2958"},"institutions":[{"id":"https://openalex.org/I2802176441","display_name":"Basque Center for Applied Mathematics","ror":"https://ror.org/03b21sh32","country_code":"ES","type":"education","lineage":["https://openalex.org/I2802176441"]}],"countries":["ES"],"is_corresponding":true,"raw_author_name":"Pratyusha Rakshit","raw_affiliation_strings":["Basque Center for Applied Mathematics, Bilbao, Spain"],"affiliations":[{"raw_affiliation_string":"Basque Center for Applied Mathematics, Bilbao, Spain","institution_ids":["https://openalex.org/I2802176441"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5011939964","display_name":"Amit Konar","orcid":"https://orcid.org/0000-0002-9474-5956"},"institutions":[{"id":"https://openalex.org/I170979836","display_name":"Jadavpur University","ror":"https://ror.org/02af4h012","country_code":"IN","type":"education","lineage":["https://openalex.org/I170979836"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Amit Konar","raw_affiliation_strings":["Department of Electronics and Telecommunication Engineering, Jadavpur University, Kolkata, India"],"affiliations":[{"raw_affiliation_string":"Department of Electronics and Telecommunication Engineering, Jadavpur University, Kolkata, India","institution_ids":["https://openalex.org/I170979836"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5081696143","display_name":"Atulya K. Nagar","orcid":"https://orcid.org/0000-0001-5549-6435"},"institutions":[{"id":"https://openalex.org/I44852757","display_name":"Liverpool Hope University","ror":"https://ror.org/03ctjbj91","country_code":"GB","type":"education","lineage":["https://openalex.org/I44852757"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Atulya K. Nagar","raw_affiliation_strings":["Department of Mathematics and Computer Science, Liverpool Hope University, United Kingdom"],"affiliations":[{"raw_affiliation_string":"Department of Mathematics and Computer Science, Liverpool Hope University, United Kingdom","institution_ids":["https://openalex.org/I44852757"]}]}],"institutions":[],"countries_distinct_count":3,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5102829523"],"corresponding_institution_ids":["https://openalex.org/I2802176441"],"apc_list":null,"apc_paid":null,"fwci":0.1326,"has_fulltext":false,"cited_by_count":4,"citation_normalized_percentile":{"value":0.54424065,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"8"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10100","display_name":"Metaheuristic Optimization Algorithms Research","score":0.9969000220298767,"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":0.9969000220298767,"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":0.9944999814033508,"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"}},{"id":"https://openalex.org/T11975","display_name":"Evolutionary Algorithms and Applications","score":0.989300012588501,"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/reinforcement-learning","display_name":"Reinforcement learning","score":0.6966195702552795},{"id":"https://openalex.org/keywords/sample","display_name":"Sample (material)","score":0.6365318298339844},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6316863894462585},{"id":"https://openalex.org/keywords/variance","display_name":"Variance (accounting)","score":0.5764926075935364},{"id":"https://openalex.org/keywords/fitness-landscape","display_name":"Fitness landscape","score":0.5746549367904663},{"id":"https://openalex.org/keywords/artificial-bee-colony-algorithm","display_name":"Artificial bee colony algorithm","score":0.5737572312355042},{"id":"https://openalex.org/keywords/noise","display_name":"Noise (video)","score":0.5541384816169739},{"id":"https://openalex.org/keywords/adaptation","display_name":"Adaptation (eye)","score":0.5449742674827576},{"id":"https://openalex.org/keywords/sample-variance","display_name":"Sample variance","score":0.526779294013977},{"id":"https://openalex.org/keywords/sample-size-determination","display_name":"Sample size determination","score":0.5198179483413696},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5078347325325012},{"id":"https://openalex.org/keywords/population","display_name":"Population","score":0.505422830581665},{"id":"https://openalex.org/keywords/mathematical-optimization","display_name":"Mathematical optimization","score":0.4822005033493042},{"id":"https://openalex.org/keywords/fitness-approximation","display_name":"Fitness approximation","score":0.44646549224853516},{"id":"https://openalex.org/keywords/fitness-function","display_name":"Fitness function","score":0.3852303624153137},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.31935209035873413},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.3053317070007324},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.27260568737983704},{"id":"https://openalex.org/keywords/genetic-algorithm","display_name":"Genetic algorithm","score":0.22021862864494324}],"concepts":[{"id":"https://openalex.org/C97541855","wikidata":"https://www.wikidata.org/wiki/Q830687","display_name":"Reinforcement learning","level":2,"score":0.6966195702552795},{"id":"https://openalex.org/C198531522","wikidata":"https://www.wikidata.org/wiki/Q485146","display_name":"Sample (material)","level":2,"score":0.6365318298339844},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6316863894462585},{"id":"https://openalex.org/C196083921","wikidata":"https://www.wikidata.org/wiki/Q7915758","display_name":"Variance (accounting)","level":2,"score":0.5764926075935364},{"id":"https://openalex.org/C91852762","wikidata":"https://www.wikidata.org/wiki/Q3307742","display_name":"Fitness landscape","level":3,"score":0.5746549367904663},{"id":"https://openalex.org/C97133563","wikidata":"https://www.wikidata.org/wiki/Q4801057","display_name":"Artificial bee colony algorithm","level":2,"score":0.5737572312355042},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.5541384816169739},{"id":"https://openalex.org/C139807058","wikidata":"https://www.wikidata.org/wiki/Q352374","display_name":"Adaptation (eye)","level":2,"score":0.5449742674827576},{"id":"https://openalex.org/C2993021520","wikidata":"https://www.wikidata.org/wiki/Q175199","display_name":"Sample variance","level":3,"score":0.526779294013977},{"id":"https://openalex.org/C129848803","wikidata":"https://www.wikidata.org/wiki/Q2564360","display_name":"Sample size determination","level":2,"score":0.5198179483413696},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5078347325325012},{"id":"https://openalex.org/C2908647359","wikidata":"https://www.wikidata.org/wiki/Q2625603","display_name":"Population","level":2,"score":0.505422830581665},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.4822005033493042},{"id":"https://openalex.org/C148392497","wikidata":"https://www.wikidata.org/wiki/Q16250539","display_name":"Fitness approximation","level":4,"score":0.44646549224853516},{"id":"https://openalex.org/C176066374","wikidata":"https://www.wikidata.org/wiki/Q629118","display_name":"Fitness function","level":3,"score":0.3852303624153137},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.31935209035873413},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.3053317070007324},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.27260568737983704},{"id":"https://openalex.org/C8880873","wikidata":"https://www.wikidata.org/wiki/Q187787","display_name":"Genetic algorithm","level":2,"score":0.22021862864494324},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C120665830","wikidata":"https://www.wikidata.org/wiki/Q14620","display_name":"Optics","level":1,"score":0.0},{"id":"https://openalex.org/C144133560","wikidata":"https://www.wikidata.org/wiki/Q4830453","display_name":"Business","level":0,"score":0.0},{"id":"https://openalex.org/C144024400","wikidata":"https://www.wikidata.org/wiki/Q21201","display_name":"Sociology","level":0,"score":0.0},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.0},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"id":"https://openalex.org/C121955636","wikidata":"https://www.wikidata.org/wiki/Q4116214","display_name":"Accounting","level":1,"score":0.0},{"id":"https://openalex.org/C43617362","wikidata":"https://www.wikidata.org/wiki/Q170050","display_name":"Chromatography","level":1,"score":0.0},{"id":"https://openalex.org/C149923435","wikidata":"https://www.wikidata.org/wiki/Q37732","display_name":"Demography","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/cec48606.2020.9185844","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cec48606.2020.9185844","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 IEEE Congress on Evolutionary Computation (CEC)","raw_type":"proceedings-article"},{"id":"pmh:oai:bird.bcamath.org:20.500.11824/1235","is_oa":false,"landing_page_url":"http://hdl.handle.net/20.500.11824/1235","pdf_url":null,"source":{"id":"https://openalex.org/S4306401608","display_name":"BIRD (Basque Center for Applied Mathematics)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I2802176441","host_organization_name":"Basque Center for Applied Mathematics","host_organization_lineage":["https://openalex.org/I2802176441"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"acceptedVersion","is_accepted":true,"is_published":false,"raw_source_name":null,"raw_type":"info:eu-repo/semantics/acceptedVersion"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":34,"referenced_works":["https://openalex.org/W659505065","https://openalex.org/W847164865","https://openalex.org/W1487312389","https://openalex.org/W1506773990","https://openalex.org/W1536615069","https://openalex.org/W1965612527","https://openalex.org/W1975906723","https://openalex.org/W1976442029","https://openalex.org/W1981663184","https://openalex.org/W1983519058","https://openalex.org/W1988465479","https://openalex.org/W1989367713","https://openalex.org/W1993131108","https://openalex.org/W2067508429","https://openalex.org/W2083532959","https://openalex.org/W2095377095","https://openalex.org/W2096166399","https://openalex.org/W2117106078","https://openalex.org/W2136827689","https://openalex.org/W2148600622","https://openalex.org/W2152043436","https://openalex.org/W2156106639","https://openalex.org/W2216771314","https://openalex.org/W2542796910","https://openalex.org/W2555395830","https://openalex.org/W2621346634","https://openalex.org/W2732143801","https://openalex.org/W2917884856","https://openalex.org/W2968140968","https://openalex.org/W3138355580","https://openalex.org/W4285719527","https://openalex.org/W6728573610","https://openalex.org/W6759768743","https://openalex.org/W6792741644"],"related_works":["https://openalex.org/W2036107212","https://openalex.org/W2164084664","https://openalex.org/W2159937791","https://openalex.org/W2138958036","https://openalex.org/W192154461","https://openalex.org/W1591022951","https://openalex.org/W1634842376","https://openalex.org/W1974337071","https://openalex.org/W4250294025","https://openalex.org/W3009038870"],"abstract_inverted_index":{"The":[0,29,52,81,109],"paper":[1],"proposes":[2],"a":[3,13,33,60,98,148],"novel":[4],"approach":[5],"to":[6,69],"adaptive":[7],"selection":[8],"of":[9,16,22,32,48,59,73,83,90,97,111,124,135,140,147],"sample":[10,30,84,127,144],"size":[11,31,85,128,145],"for":[12,126],"trial":[14],"solution":[15,34,65,99,149],"an":[17],"evolutionary":[18],"algorithm":[19],"when":[20],"noise":[21,74],"unknown":[23],"distribution":[24],"contaminates":[25],"the":[26,40,45,49,56,63,71,88,91,95,104,112,118,132,143,151,162,172,176],"objective":[27],"surface.":[28],"here":[35,102],"is":[36,100],"adapted":[37],"based":[38,86,120],"on":[39,87],"noisy":[41,152],"fitness":[42,53,57,92,153],"profile":[43,154],"in":[44,76,94,116,155],"local":[46,78],"surrounding":[47,62],"given":[50,64],"solution.":[51],"estimate":[54],"and":[55,150,175],"variance":[58],"sub-population":[61],"are":[66],"jointly":[67],"used":[68],"signify":[70],"degree":[72],"contamination":[75],"its":[77,156],"neighborhood":[79],"(LN).":[80],"adaptation":[82],"characteristics":[89],"landscape":[93],"LN":[96],"realized":[101,165],"with":[103,166],"temporal":[105],"difference":[106],"Q-learning":[107],"(TDQL).":[108],"merit":[110],"present":[113],"work":[114],"lies":[115],"utilizing":[117],"reward-penalty":[119],"reinforcement":[121],"learning":[122],"mechanism":[123],"TDQL":[125],"adaptation.":[129],"This":[130],"sidesteps":[131],"prerequisite":[133],"setting":[134],"any":[136],"specific":[137],"functional":[138],"form":[139],"relationship":[141],"between":[142],"requirement":[146],"LN.":[157],"Experiments":[158],"undertaken":[159],"reveal":[160],"that":[161],"proposed":[163],"algorithms,":[164],"artificial":[167],"bee":[168],"colony,":[169],"significantly":[170],"outperform":[171],"existing":[173],"counterparts":[174],"state-of-the-art":[177],"algorithms.":[178]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":1},{"year":2022,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
