{"id":"https://openalex.org/W1973744814","doi":"https://doi.org/10.1145/2001576.2001853","title":"The effects of selection on noisy fitness optimization","display_name":"The effects of selection on noisy fitness optimization","publication_year":2011,"publication_date":"2011-07-12","ids":{"openalex":"https://openalex.org/W1973744814","doi":"https://doi.org/10.1145/2001576.2001853","mag":"1973744814"},"language":"en","primary_location":{"id":"doi:10.1145/2001576.2001853","is_oa":false,"landing_page_url":"https://doi.org/10.1145/2001576.2001853","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 13th annual conference on Genetic and evolutionary computation","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/A5058953553","display_name":"Sergiu Goschin","orcid":null},"institutions":[{"id":"https://openalex.org/I102322142","display_name":"Rutgers, The State University of New Jersey","ror":"https://ror.org/05vt9qd57","country_code":"US","type":"education","lineage":["https://openalex.org/I102322142"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Sergiu Goschin","raw_affiliation_strings":["Rutgers University, Piscataway, NJ, USA","Rutgers University , Piscataway, NJ , USA ,"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Rutgers University, Piscataway, NJ, USA","institution_ids":["https://openalex.org/I102322142"]},{"raw_affiliation_string":"Rutgers University , Piscataway, NJ , USA ,","institution_ids":["https://openalex.org/I102322142"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5009722403","display_name":"Michael L. Littman","orcid":"https://orcid.org/0000-0002-5596-1840"},"institutions":[{"id":"https://openalex.org/I102322142","display_name":"Rutgers, The State University of New Jersey","ror":"https://ror.org/05vt9qd57","country_code":"US","type":"education","lineage":["https://openalex.org/I102322142"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Michael L. Littman","raw_affiliation_strings":["Rutgers University, Piscataway, NJ, USA","Rutgers University , Piscataway, NJ , USA ,"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Rutgers University, Piscataway, NJ, USA","institution_ids":["https://openalex.org/I102322142"]},{"raw_affiliation_string":"Rutgers University , Piscataway, NJ , USA ,","institution_ids":["https://openalex.org/I102322142"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5014696096","display_name":"David H. Ackley","orcid":null},"institutions":[{"id":"https://openalex.org/I169521973","display_name":"University of New Mexico","ror":"https://ror.org/05fs6jp91","country_code":"US","type":"education","lineage":["https://openalex.org/I169521973"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"David H. Ackley","raw_affiliation_strings":["University of New Mexico, Albuquerque, NM, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of New Mexico, Albuquerque, NM, USA","institution_ids":["https://openalex.org/I169521973"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":1.7586,"has_fulltext":false,"cited_by_count":5,"citation_normalized_percentile":{"value":0.86401899,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":96},"biblio":{"volume":null,"issue":null,"first_page":"2059","last_page":"2066"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10100","display_name":"Metaheuristic Optimization Algorithms Research","score":0.9983999729156494,"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":0.9983999729156494,"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":0.9983000159263611,"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/T11252","display_name":"Evolutionary Game Theory and Cooperation","score":0.9934999942779541,"subfield":{"id":"https://openalex.org/subfields/3312","display_name":"Sociology and Political Science"},"field":{"id":"https://openalex.org/fields/33","display_name":"Social Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/tournament-selection","display_name":"Tournament selection","score":0.9001694321632385},{"id":"https://openalex.org/keywords/selection","display_name":"Selection (genetic algorithm)","score":0.7823113799095154},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.6966825127601624},{"id":"https://openalex.org/keywords/fitness-proportionate-selection","display_name":"Fitness proportionate selection","score":0.667190432548523},{"id":"https://openalex.org/keywords/truncation","display_name":"Truncation (statistics)","score":0.6390172243118286},{"id":"https://openalex.org/keywords/truncation-selection","display_name":"Truncation selection","score":0.6147145628929138},{"id":"https://openalex.org/keywords/fitness-function","display_name":"Fitness function","score":0.5991141200065613},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.596796452999115},{"id":"https://openalex.org/keywords/population","display_name":"Population","score":0.5795853734016418},{"id":"https://openalex.org/keywords/mathematical-optimization","display_name":"Mathematical optimization","score":0.5541083216667175},{"id":"https://openalex.org/keywords/evolutionary-algorithm","display_name":"Evolutionary algorithm","score":0.4609454572200775},{"id":"https://openalex.org/keywords/function","display_name":"Function (biology)","score":0.4268420338630676},{"id":"https://openalex.org/keywords/tournament","display_name":"Tournament","score":0.4218185842037201},{"id":"https://openalex.org/keywords/optimization-problem","display_name":"Optimization problem","score":0.4179854393005371},{"id":"https://openalex.org/keywords/fitness-approximation","display_name":"Fitness approximation","score":0.4103517234325409},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.30001047253608704},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.27251774072647095},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.2405065894126892},{"id":"https://openalex.org/keywords/genetic-algorithm","display_name":"Genetic algorithm","score":0.19927236437797546},{"id":"https://openalex.org/keywords/biology","display_name":"Biology","score":0.06327313184738159}],"concepts":[{"id":"https://openalex.org/C165661538","wikidata":"https://www.wikidata.org/wiki/Q7829327","display_name":"Tournament selection","level":3,"score":0.9001694321632385},{"id":"https://openalex.org/C81917197","wikidata":"https://www.wikidata.org/wiki/Q628760","display_name":"Selection (genetic algorithm)","level":2,"score":0.7823113799095154},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.6966825127601624},{"id":"https://openalex.org/C99701942","wikidata":"https://www.wikidata.org/wiki/Q5455479","display_name":"Fitness proportionate selection","level":4,"score":0.667190432548523},{"id":"https://openalex.org/C106195933","wikidata":"https://www.wikidata.org/wiki/Q7847935","display_name":"Truncation (statistics)","level":2,"score":0.6390172243118286},{"id":"https://openalex.org/C106284839","wikidata":"https://www.wikidata.org/wiki/Q7847936","display_name":"Truncation selection","level":3,"score":0.6147145628929138},{"id":"https://openalex.org/C176066374","wikidata":"https://www.wikidata.org/wiki/Q629118","display_name":"Fitness function","level":3,"score":0.5991141200065613},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.596796452999115},{"id":"https://openalex.org/C2908647359","wikidata":"https://www.wikidata.org/wiki/Q2625603","display_name":"Population","level":2,"score":0.5795853734016418},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.5541083216667175},{"id":"https://openalex.org/C159149176","wikidata":"https://www.wikidata.org/wiki/Q14489129","display_name":"Evolutionary algorithm","level":2,"score":0.4609454572200775},{"id":"https://openalex.org/C14036430","wikidata":"https://www.wikidata.org/wiki/Q3736076","display_name":"Function (biology)","level":2,"score":0.4268420338630676},{"id":"https://openalex.org/C136975688","wikidata":"https://www.wikidata.org/wiki/Q1320634","display_name":"Tournament","level":2,"score":0.4218185842037201},{"id":"https://openalex.org/C137836250","wikidata":"https://www.wikidata.org/wiki/Q984063","display_name":"Optimization problem","level":2,"score":0.4179854393005371},{"id":"https://openalex.org/C148392497","wikidata":"https://www.wikidata.org/wiki/Q16250539","display_name":"Fitness approximation","level":4,"score":0.4103517234325409},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.30001047253608704},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.27251774072647095},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.2405065894126892},{"id":"https://openalex.org/C8880873","wikidata":"https://www.wikidata.org/wiki/Q187787","display_name":"Genetic algorithm","level":2,"score":0.19927236437797546},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.06327313184738159},{"id":"https://openalex.org/C144024400","wikidata":"https://www.wikidata.org/wiki/Q21201","display_name":"Sociology","level":0,"score":0.0},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"score":0.0},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.0},{"id":"https://openalex.org/C13280743","wikidata":"https://www.wikidata.org/wiki/Q131089","display_name":"Geodesy","level":1,"score":0.0},{"id":"https://openalex.org/C78458016","wikidata":"https://www.wikidata.org/wiki/Q840400","display_name":"Evolutionary biology","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:10.1145/2001576.2001853","is_oa":false,"landing_page_url":"https://doi.org/10.1145/2001576.2001853","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 13th annual conference on Genetic and evolutionary computation","raw_type":"proceedings-article"},{"id":"pmh:oai:CiteSeerX.psu:10.1.1.700.2859","is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.700.2859","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://paul.rutgers.edu/%7Esgoschin/papers/GECCO_2011.pdf","raw_type":"text"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":15,"referenced_works":["https://openalex.org/W157468466","https://openalex.org/W183421984","https://openalex.org/W1487312389","https://openalex.org/W1499983649","https://openalex.org/W1528423931","https://openalex.org/W1598952354","https://openalex.org/W1976379984","https://openalex.org/W2028335093","https://openalex.org/W2059654640","https://openalex.org/W2149125415","https://openalex.org/W2154929945","https://openalex.org/W2156106639","https://openalex.org/W2166655039","https://openalex.org/W2320735730","https://openalex.org/W6635959259"],"related_works":["https://openalex.org/W4200573379","https://openalex.org/W1589065806","https://openalex.org/W2071806120","https://openalex.org/W193363969","https://openalex.org/W2050206882","https://openalex.org/W4285805368","https://openalex.org/W2350426988","https://openalex.org/W2135808265","https://openalex.org/W1599846717","https://openalex.org/W1973744814"],"abstract_inverted_index":{"This":[0],"paper":[1],"examines":[2],"how":[3],"the":[4,7,15,22,60],"choice":[5,61],"of":[6,62,103,105],"selection":[8,39,44,50,63],"mechanism":[9],"in":[10,33,55,73],"an":[11,34],"evolutionary":[12],"algorithm":[13],"impacts":[14],"objective":[16],"function":[17,24],"it":[18],"optimizes,":[19],"specifically":[20],"when":[21,66],"fitness":[23,67],"is":[25],"noisy.":[26],"We":[27],"provide":[28],"formal":[29],"results":[30,83],"showing":[31],"that,":[32],"abstract":[35],"infinite-population":[36],"model,":[37],"proportional":[38],"optimizes":[40,45],"expected":[41],"fitness,":[42],"truncation":[43],"order":[46],"statistics,":[47],"and":[48],"tournament":[49],"can":[51],"oscillate.":[52],"The":[53],"\"winner\"":[54],"a":[56,85,101],"population":[57],"depends":[58],"on":[59,84],"rule,":[64],"especially":[65],"distributions":[68],"differ":[69],"between":[70],"individuals":[71],"resulting":[72],"variable":[74],"risk.":[75],"These":[76],"findings":[77],"are":[78],"further":[79],"developed":[80],"through":[81],"empirical":[82],"novel":[86],"stochastic":[87],"optimization":[88],"problem":[89],"called":[90],"\"Die4\",":[91],"which,":[92],"while":[93],"simple,":[94],"extends":[95],"existing":[96],"benchmark":[97],"problems":[98],"by":[99],"admitting":[100],"variety":[102],"interpretations":[104],"optimality.":[106]},"counts_by_year":[{"year":2016,"cited_by_count":1},{"year":2014,"cited_by_count":2},{"year":2013,"cited_by_count":2}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}