{"id":"https://openalex.org/W4285805230","doi":"https://doi.org/10.1145/3520304.3534061","title":"Measuring the ability of lexicase selection to find obscure pathways to optimality","display_name":"Measuring the ability of lexicase selection to find obscure pathways to optimality","publication_year":2022,"publication_date":"2022-07-09","ids":{"openalex":"https://openalex.org/W4285805230","doi":"https://doi.org/10.1145/3520304.3534061"},"language":"en","primary_location":{"id":"doi:10.1145/3520304.3534061","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3520304.3534061","pdf_url":"https://dl.acm.org/action/downloadSupplement?doi=10.1145%2F3520304.3534061&file=p21-hernandez-suppl.pdf","source":{"id":"https://openalex.org/S4363608771","display_name":"Proceedings of the Genetic and Evolutionary Computation Conference Companion","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Genetic and Evolutionary Computation Conference Companion","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"bronze","oa_url":"https://dl.acm.org/action/downloadSupplement?doi=10.1145%2F3520304.3534061&file=p21-hernandez-suppl.pdf","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5049564563","display_name":"Jose Guadalupe Hernandez","orcid":"https://orcid.org/0000-0002-1298-5551"},"institutions":[{"id":"https://openalex.org/I87216513","display_name":"Michigan State University","ror":"https://ror.org/05hs6h993","country_code":"US","type":"education","lineage":["https://openalex.org/I87216513"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Jose Guadalupe Hernandez","raw_affiliation_strings":["Michigan State University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Michigan State University","institution_ids":["https://openalex.org/I87216513"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5008242968","display_name":"Alexander Lalejini","orcid":"https://orcid.org/0000-0003-0994-2718"},"institutions":[{"id":"https://openalex.org/I27837315","display_name":"University of Michigan","ror":"https://ror.org/00jmfr291","country_code":"US","type":"education","lineage":["https://openalex.org/I27837315"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Alexander Lalejini","raw_affiliation_strings":["University of Michigan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Michigan","institution_ids":["https://openalex.org/I27837315"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5026353119","display_name":"Charles Ofria","orcid":"https://orcid.org/0000-0003-2924-1732"},"institutions":[{"id":"https://openalex.org/I87216513","display_name":"Michigan State University","ror":"https://ror.org/05hs6h993","country_code":"US","type":"education","lineage":["https://openalex.org/I87216513"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Charles Ofria","raw_affiliation_strings":["Michigan State University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Michigan State University","institution_ids":["https://openalex.org/I87216513"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.1038,"has_fulltext":true,"cited_by_count":1,"citation_normalized_percentile":{"value":0.2671084,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":95},"biblio":{"volume":null,"issue":null,"first_page":"21","last_page":"22"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11975","display_name":"Evolutionary Algorithms and Applications","score":0.9994999766349792,"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/T11975","display_name":"Evolutionary Algorithms and Applications","score":0.9994999766349792,"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/T10100","display_name":"Metaheuristic Optimization Algorithms Research","score":0.991100013256073,"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/T10878","display_name":"CRISPR and Genetic Engineering","score":0.9887999892234802,"subfield":{"id":"https://openalex.org/subfields/1312","display_name":"Molecular Biology"},"field":{"id":"https://openalex.org/fields/13","display_name":"Biochemistry, Genetics and Molecular Biology"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/selection","display_name":"Selection (genetic algorithm)","score":0.795441746711731},{"id":"https://openalex.org/keywords/novelty","display_name":"Novelty","score":0.6817960739135742},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6257975101470947},{"id":"https://openalex.org/keywords/population","display_name":"Population","score":0.5224512815475464},{"id":"https://openalex.org/keywords/space","display_name":"Space (punctuation)","score":0.48712825775146484},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.42196816205978394},{"id":"https://openalex.org/keywords/fitness-proportionate-selection","display_name":"Fitness proportionate selection","score":0.4172220826148987},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.38368934392929077},{"id":"https://openalex.org/keywords/mathematical-optimization","display_name":"Mathematical optimization","score":0.35231995582580566},{"id":"https://openalex.org/keywords/genetic-algorithm","display_name":"Genetic algorithm","score":0.29659736156463623},{"id":"https://openalex.org/keywords/fitness-function","display_name":"Fitness function","score":0.2328384816646576},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.2240816354751587}],"concepts":[{"id":"https://openalex.org/C81917197","wikidata":"https://www.wikidata.org/wiki/Q628760","display_name":"Selection (genetic algorithm)","level":2,"score":0.795441746711731},{"id":"https://openalex.org/C2778738651","wikidata":"https://www.wikidata.org/wiki/Q16546687","display_name":"Novelty","level":2,"score":0.6817960739135742},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6257975101470947},{"id":"https://openalex.org/C2908647359","wikidata":"https://www.wikidata.org/wiki/Q2625603","display_name":"Population","level":2,"score":0.5224512815475464},{"id":"https://openalex.org/C2778572836","wikidata":"https://www.wikidata.org/wiki/Q380933","display_name":"Space (punctuation)","level":2,"score":0.48712825775146484},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.42196816205978394},{"id":"https://openalex.org/C99701942","wikidata":"https://www.wikidata.org/wiki/Q5455479","display_name":"Fitness proportionate selection","level":4,"score":0.4172220826148987},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.38368934392929077},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.35231995582580566},{"id":"https://openalex.org/C8880873","wikidata":"https://www.wikidata.org/wiki/Q187787","display_name":"Genetic algorithm","level":2,"score":0.29659736156463623},{"id":"https://openalex.org/C176066374","wikidata":"https://www.wikidata.org/wiki/Q629118","display_name":"Fitness function","level":3,"score":0.2328384816646576},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.2240816354751587},{"id":"https://openalex.org/C149923435","wikidata":"https://www.wikidata.org/wiki/Q37732","display_name":"Demography","level":1,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","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/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0},{"id":"https://openalex.org/C27206212","wikidata":"https://www.wikidata.org/wiki/Q34178","display_name":"Theology","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3520304.3534061","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3520304.3534061","pdf_url":"https://dl.acm.org/action/downloadSupplement?doi=10.1145%2F3520304.3534061&file=p21-hernandez-suppl.pdf","source":{"id":"https://openalex.org/S4363608771","display_name":"Proceedings of the Genetic and Evolutionary Computation Conference Companion","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Genetic and Evolutionary Computation Conference Companion","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.1145/3520304.3534061","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3520304.3534061","pdf_url":"https://dl.acm.org/action/downloadSupplement?doi=10.1145%2F3520304.3534061&file=p21-hernandez-suppl.pdf","source":{"id":"https://openalex.org/S4363608771","display_name":"Proceedings of the Genetic and Evolutionary Computation Conference Companion","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Genetic and Evolutionary Computation Conference Companion","raw_type":"proceedings-article"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G7414076325","display_name":null,"funder_award_id":"DBI-0939454","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"}],"funders":[{"id":"https://openalex.org/F4320306076","display_name":"National Science Foundation","ror":"https://ror.org/021nxhr62"}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4285805230.pdf","grobid_xml":"https://content.openalex.org/works/W4285805230.grobid-xml"},"referenced_works_count":4,"referenced_works":["https://openalex.org/W1978661986","https://openalex.org/W2830196635","https://openalex.org/W3184917773","https://openalex.org/W4289305969"],"related_works":["https://openalex.org/W2961085424","https://openalex.org/W2033570426","https://openalex.org/W4200573379","https://openalex.org/W2037594302","https://openalex.org/W4306674287","https://openalex.org/W2350426988","https://openalex.org/W2545929163","https://openalex.org/W4224009465","https://openalex.org/W2367645460","https://openalex.org/W4285805230"],"abstract_inverted_index":{"This":[0],"Hot-off-the-Press":[1],"paper":[2],"summarizes":[3],"our":[4,92],"recently":[5],"published":[6,24],"work,":[7],"\"An":[8],"Exploration":[9],"of":[10,15,100,105,148,182,208],"Exploration:":[11],"Measuring":[12],"the":[13,97,140,146,206],"Ability":[14],"Lexicase":[16],"Selection":[17],"to":[18,22,82,95,132,139,186],"Find":[19],"Obscure":[20],"Pathways":[21],"Optimality,\"":[23],"as":[25],"a":[26,44,60,78,87,134],"chapter":[27],"in":[28,86],"Genetic":[29],"Programming":[30],"Theory":[31],"and":[32,103,114,125,145,178],"Practice":[33],"XVIII":[34],"[3].":[35],"In":[36,69],"evolutionary":[37],"search,":[38],"selection":[39,61,79,102,121],"schemes":[40],"drive":[41],"populations":[42],"through":[43],"problem's":[45],"search":[46,64,88,135,169],"space,":[47],"often":[48],"trading":[49],"off":[50],"exploitation":[51,66],"with":[52,67,163],"exploration.":[53,68,171],"Indeed,":[54],"problem-solving":[55],"success":[56],"depends":[57],"on":[58],"how":[59],"scheme":[62],"balances":[63],"space":[65,136,170],"[3],":[70],"we":[71,126,173,202],"introduce":[72],"an":[73],"\"exploration":[74],"diagnostic\"":[75],"that":[76,119,128,158,175,205],"measures":[77],"scheme's":[80],"ability":[81,131],"explore":[83,133],"different":[84],"pathways":[85],"space.":[89],"We":[90,117,156],"use":[91],"exploration":[93,198],"diagnostic":[94],"investigate":[96],"exploratory":[98,191,216],"capacity":[99],"lexicase":[101,120,129,160,165,214],"several":[104],"its":[106],"variants:":[107],"epsilon":[108,164],"lexicase,":[109,111,113],"down-sampled":[110,177],"cohort":[112,179,194],"novelty":[115],"lexicase.":[116],"verify":[118],"out-explores":[122],"tournament":[123],"selection,":[124],"demonstrate":[127],"selection's":[130,161,215],"is":[137],"sensitive":[138],"ratio":[141],"between":[142],"population":[143],"size":[144],"number":[147],"test":[149,187,210],"cases":[150,211],"used":[151],"for":[152],"evaluating":[153],"candidate":[154],"solutions.":[155],"find":[157,174,203],"relaxing":[159],"elitism":[162],"can":[166,212],"further":[167],"improve":[168],"Additionally,":[172],"both":[176],"lexicase---two":[180],"methods":[181],"applying":[183],"random":[184],"subsampling":[185],"cases---substantially":[188],"degrade":[189,213],"lexicase's":[190],"capacity;":[192],"however,":[193],"partitioning":[195],"better":[196],"preserves":[197],"than":[199],"down-sampling.":[200],"Finally,":[201],"evidence":[204],"addition":[207],"novelty-based":[209],"capacity.":[217]},"counts_by_year":[{"year":2025,"cited_by_count":1}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}
