{"id":"https://openalex.org/W2119653020","doi":"https://doi.org/10.1145/1830483.1830652","title":"Predicting solution rank to improve performance","display_name":"Predicting solution rank to improve performance","publication_year":2010,"publication_date":"2010-07-07","ids":{"openalex":"https://openalex.org/W2119653020","doi":"https://doi.org/10.1145/1830483.1830652","mag":"2119653020"},"language":"en","primary_location":{"id":"doi:10.1145/1830483.1830652","is_oa":false,"landing_page_url":"https://doi.org/10.1145/1830483.1830652","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 12th annual conference on Genetic and evolutionary computation","raw_type":"proceedings-article"},"type":"conference-paper","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/A5088013683","display_name":"Michael D. Schmidt","orcid":"https://orcid.org/0000-0002-8062-4491"},"institutions":[{"id":"https://openalex.org/I205783295","display_name":"Cornell University","ror":"https://ror.org/05bnh6r87","country_code":"US","type":"education","lineage":["https://openalex.org/I205783295"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Michael D. Schmidt","raw_affiliation_strings":["Cornell University, Ithaca, NY, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Cornell University, Ithaca, NY, USA","institution_ids":["https://openalex.org/I205783295"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5025894735","display_name":"Hod Lipson","orcid":"https://orcid.org/0000-0003-0769-4618"},"institutions":[{"id":"https://openalex.org/I205783295","display_name":"Cornell University","ror":"https://ror.org/05bnh6r87","country_code":"US","type":"education","lineage":["https://openalex.org/I205783295"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Hod Lipson","raw_affiliation_strings":["Cornell University, Ithaca, NY, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Cornell University, Ithaca, NY, USA","institution_ids":["https://openalex.org/I205783295"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I205783295"],"apc_list":null,"apc_paid":null,"fwci":1.3623,"has_fulltext":false,"cited_by_count":11,"citation_normalized_percentile":{"value":0.82306724,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":96},"biblio":{"volume":null,"issue":null,"first_page":"949","last_page":"956"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11975","display_name":"Evolutionary Algorithms and Applications","score":0.9995999932289124,"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":0.9995999932289124,"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/T11349","display_name":"Music Technology and Sound Studies","score":0.9829999804496765,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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/T11309","display_name":"Music and Audio Processing","score":0.9811000227928162,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"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/rank","display_name":"Rank (graph theory)","score":0.7711488008499146},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.7589306831359863},{"id":"https://openalex.org/keywords/convergence","display_name":"Convergence (economics)","score":0.6655769348144531},{"id":"https://openalex.org/keywords/symbolic-regression","display_name":"Symbolic regression","score":0.5936623811721802},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5793702006340027},{"id":"https://openalex.org/keywords/population","display_name":"Population","score":0.5283870100975037},{"id":"https://openalex.org/keywords/fitness-approximation","display_name":"Fitness approximation","score":0.47326138615608215},{"id":"https://openalex.org/keywords/evolutionary-algorithm","display_name":"Evolutionary algorithm","score":0.4598016142845154},{"id":"https://openalex.org/keywords/regression","display_name":"Regression","score":0.4449799656867981},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4333280026912689},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4329301714897156},{"id":"https://openalex.org/keywords/mathematical-optimization","display_name":"Mathematical optimization","score":0.41880926489830017},{"id":"https://openalex.org/keywords/evolutionary-computation","display_name":"Evolutionary computation","score":0.415584534406662},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.37707820534706116},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.32285574078559875},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.20765841007232666},{"id":"https://openalex.org/keywords/genetic-algorithm","display_name":"Genetic algorithm","score":0.12955385446548462},{"id":"https://openalex.org/keywords/genetic-programming","display_name":"Genetic programming","score":0.12278345227241516},{"id":"https://openalex.org/keywords/fitness-function","display_name":"Fitness function","score":0.11703956127166748}],"concepts":[{"id":"https://openalex.org/C164226766","wikidata":"https://www.wikidata.org/wiki/Q7293202","display_name":"Rank (graph theory)","level":2,"score":0.7711488008499146},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.7589306831359863},{"id":"https://openalex.org/C2777303404","wikidata":"https://www.wikidata.org/wiki/Q759757","display_name":"Convergence (economics)","level":2,"score":0.6655769348144531},{"id":"https://openalex.org/C2776400721","wikidata":"https://www.wikidata.org/wiki/Q18171762","display_name":"Symbolic regression","level":3,"score":0.5936623811721802},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5793702006340027},{"id":"https://openalex.org/C2908647359","wikidata":"https://www.wikidata.org/wiki/Q2625603","display_name":"Population","level":2,"score":0.5283870100975037},{"id":"https://openalex.org/C148392497","wikidata":"https://www.wikidata.org/wiki/Q16250539","display_name":"Fitness approximation","level":4,"score":0.47326138615608215},{"id":"https://openalex.org/C159149176","wikidata":"https://www.wikidata.org/wiki/Q14489129","display_name":"Evolutionary algorithm","level":2,"score":0.4598016142845154},{"id":"https://openalex.org/C83546350","wikidata":"https://www.wikidata.org/wiki/Q1139051","display_name":"Regression","level":2,"score":0.4449799656867981},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4333280026912689},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4329301714897156},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.41880926489830017},{"id":"https://openalex.org/C105902424","wikidata":"https://www.wikidata.org/wiki/Q1197129","display_name":"Evolutionary computation","level":2,"score":0.415584534406662},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.37707820534706116},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.32285574078559875},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.20765841007232666},{"id":"https://openalex.org/C8880873","wikidata":"https://www.wikidata.org/wiki/Q187787","display_name":"Genetic algorithm","level":2,"score":0.12955385446548462},{"id":"https://openalex.org/C110332635","wikidata":"https://www.wikidata.org/wiki/Q629498","display_name":"Genetic programming","level":2,"score":0.12278345227241516},{"id":"https://openalex.org/C176066374","wikidata":"https://www.wikidata.org/wiki/Q629118","display_name":"Fitness function","level":3,"score":0.11703956127166748},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","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/C50522688","wikidata":"https://www.wikidata.org/wiki/Q189833","display_name":"Economic growth","level":1,"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/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/C149923435","wikidata":"https://www.wikidata.org/wiki/Q37732","display_name":"Demography","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1145/1830483.1830652","is_oa":false,"landing_page_url":"https://doi.org/10.1145/1830483.1830652","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 12th annual conference on Genetic and evolutionary computation","raw_type":"proceedings-article"},{"id":"pmh:oai:CiteSeerX.psu:10.1.1.375.8444","is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.375.8444","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://creativemachines.cornell.edu/sites/default/files/p949-schmidt.pdf","raw_type":"text"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":27,"referenced_works":["https://openalex.org/W1483317606","https://openalex.org/W1520622896","https://openalex.org/W1540706608","https://openalex.org/W1565220935","https://openalex.org/W1576818901","https://openalex.org/W1585335425","https://openalex.org/W1607481666","https://openalex.org/W1608172944","https://openalex.org/W1961183092","https://openalex.org/W1961482980","https://openalex.org/W1979769287","https://openalex.org/W2012451526","https://openalex.org/W2013695155","https://openalex.org/W2015150738","https://openalex.org/W2023816283","https://openalex.org/W2086694237","https://openalex.org/W2091338396","https://openalex.org/W2092265068","https://openalex.org/W2092582887","https://openalex.org/W2093828424","https://openalex.org/W2097204767","https://openalex.org/W2143810412","https://openalex.org/W2144315657","https://openalex.org/W2151019861","https://openalex.org/W2156106639","https://openalex.org/W2170808194","https://openalex.org/W2414365832"],"related_works":["https://openalex.org/W1583704618","https://openalex.org/W4297582752","https://openalex.org/W4285805405","https://openalex.org/W2012451526","https://openalex.org/W1792573625","https://openalex.org/W1606502848","https://openalex.org/W1594431409","https://openalex.org/W2391924736","https://openalex.org/W3133779647","https://openalex.org/W1560122427"],"abstract_inverted_index":{"Many":[0],"applications":[1],"of":[2,14,33,82],"evolutionary":[3],"algorithms":[4],"utilize":[5],"fitness":[6,41,115],"approximations,":[7],"for":[8,103],"example":[9],"coarse-grained":[10],"simulations":[11],"in":[12,86,100],"lieu":[13],"computationally":[15],"intensive":[16],"simulations.":[17],"Here,":[18],"we":[19],"propose":[20],"that":[21,28,47,68],"it":[22],"is":[23],"better":[24],"to":[25,53,71],"learn":[26],"approximations":[27],"accurately":[29,54],"predict":[30],"the":[31,56,77],"ranks":[32],"individuals":[34],"rather":[35],"than":[36,114],"explicitly":[37],"estimating":[38],"their":[39],"real-valued":[40,73],"values.":[42],"We":[43,60,75],"present":[44],"an":[45],"algorithm":[46,67],"coevolves":[48],"a":[49,65,97],"rank-predictor":[50],"which":[51],"optimizes":[52],"rank":[55,93],"evolving":[57],"solution":[58],"population.":[59],"compare":[61],"this":[62],"method":[63,95],"with":[64,89],"similar":[66,104],"uses":[69],"fitness-predictors":[70],"approximate":[72],"fitnesses.":[74],"benchmark":[76],"two":[78],"approaches":[79],"using":[80],"thousands":[81],"randomly-generated":[83],"test":[84],"problems":[85],"Symbolic":[87],"Regression":[88],"varying":[90],"difficulties.":[91],"The":[92],"prediction":[94,108],"showed":[96],"5-fold":[98],"reduction":[99],"computational":[101],"effort":[102],"convergence":[105],"rates.":[106],"Rank":[107],"also":[109],"produced":[110],"less":[111],"bloated":[112],"solutions":[113],"prediction.":[116]},"counts_by_year":[{"year":2021,"cited_by_count":2},{"year":2019,"cited_by_count":2},{"year":2015,"cited_by_count":1},{"year":2013,"cited_by_count":1},{"year":2012,"cited_by_count":2}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}