{"id":"https://openalex.org/W2084336898","doi":"https://doi.org/10.1145/2464576.2482702","title":"Comparison of two methods for computing action values in XCS with code-fragment actions","display_name":"Comparison of two methods for computing action values in XCS with code-fragment actions","publication_year":2013,"publication_date":"2013-07-06","ids":{"openalex":"https://openalex.org/W2084336898","doi":"https://doi.org/10.1145/2464576.2482702","mag":"2084336898"},"language":"en","primary_location":{"id":"doi:10.1145/2464576.2482702","is_oa":false,"landing_page_url":"https://doi.org/10.1145/2464576.2482702","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 15th annual conference companion 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/A5100733262","display_name":"Muhammad Iqbal","orcid":"https://orcid.org/0000-0001-9004-5453"},"institutions":[{"id":"https://openalex.org/I41156924","display_name":"Victoria University of Wellington","ror":"https://ror.org/0040r6f76","country_code":"NZ","type":"education","lineage":["https://openalex.org/I41156924"]}],"countries":["NZ"],"is_corresponding":false,"raw_author_name":"Muhammad Iqbal","raw_affiliation_strings":["Victoria University of Wellington, Wellington, New Zealand"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Victoria University of Wellington, Wellington, New Zealand","institution_ids":["https://openalex.org/I41156924"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5065533636","display_name":"Will N. Browne","orcid":"https://orcid.org/0000-0001-8979-2224"},"institutions":[{"id":"https://openalex.org/I41156924","display_name":"Victoria University of Wellington","ror":"https://ror.org/0040r6f76","country_code":"NZ","type":"education","lineage":["https://openalex.org/I41156924"]}],"countries":["NZ"],"is_corresponding":false,"raw_author_name":"Will N. Browne","raw_affiliation_strings":["Victoria University of Wellington, Wellington, New Zealand"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Victoria University of Wellington, Wellington, New Zealand","institution_ids":["https://openalex.org/I41156924"]}]},{"author_position":"last","author":{"id":null,"display_name":"Mengjie Zhang","orcid":null},"institutions":[{"id":"https://openalex.org/I41156924","display_name":"Victoria University of Wellington","ror":"https://ror.org/0040r6f76","country_code":"NZ","type":"education","lineage":["https://openalex.org/I41156924"]}],"countries":["NZ"],"is_corresponding":false,"raw_author_name":"Mengjie Zhang","raw_affiliation_strings":["Victoria University of Wellington, Wellington, New Zealand"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Victoria University of Wellington, Wellington, New Zealand","institution_ids":["https://openalex.org/I41156924"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I41156924"],"apc_list":null,"apc_paid":null,"fwci":0.9152,"has_fulltext":false,"cited_by_count":7,"citation_normalized_percentile":{"value":0.75341795,"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":"1235","last_page":"1242"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11975","display_name":"Evolutionary Algorithms and Applications","score":0.9998999834060669,"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":0.9998999834060669,"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":0.9801999926567078,"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":0.9799000024795532,"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/classifier","display_name":"Classifier (UML)","score":0.7895146608352661},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6166860461235046},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5917699933052063},{"id":"https://openalex.org/keywords/genetic-programming","display_name":"Genetic programming","score":0.5866215825080872},{"id":"https://openalex.org/keywords/margin-classifier","display_name":"Margin classifier","score":0.5723059177398682},{"id":"https://openalex.org/keywords/quadratic-classifier","display_name":"Quadratic classifier","score":0.5378709435462952},{"id":"https://openalex.org/keywords/random-subspace-method","display_name":"Random subspace method","score":0.47087228298187256},{"id":"https://openalex.org/keywords/binary-number","display_name":"Binary number","score":0.4118947386741638},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.408460408449173},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.37353187799453735},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.33029526472091675},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.3289874196052551},{"id":"https://openalex.org/keywords/arithmetic","display_name":"Arithmetic","score":0.0888836681842804}],"concepts":[{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.7895146608352661},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6166860461235046},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5917699933052063},{"id":"https://openalex.org/C110332635","wikidata":"https://www.wikidata.org/wiki/Q629498","display_name":"Genetic programming","level":2,"score":0.5866215825080872},{"id":"https://openalex.org/C173102733","wikidata":"https://www.wikidata.org/wiki/Q6760396","display_name":"Margin classifier","level":3,"score":0.5723059177398682},{"id":"https://openalex.org/C52620605","wikidata":"https://www.wikidata.org/wiki/Q7268357","display_name":"Quadratic classifier","level":3,"score":0.5378709435462952},{"id":"https://openalex.org/C106135958","wikidata":"https://www.wikidata.org/wiki/Q7291993","display_name":"Random subspace method","level":3,"score":0.47087228298187256},{"id":"https://openalex.org/C48372109","wikidata":"https://www.wikidata.org/wiki/Q3913","display_name":"Binary number","level":2,"score":0.4118947386741638},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.408460408449173},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.37353187799453735},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.33029526472091675},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.3289874196052551},{"id":"https://openalex.org/C94375191","wikidata":"https://www.wikidata.org/wiki/Q11205","display_name":"Arithmetic","level":1,"score":0.0888836681842804}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/2464576.2482702","is_oa":false,"landing_page_url":"https://doi.org/10.1145/2464576.2482702","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 15th annual conference companion on Genetic and evolutionary computation","raw_type":"proceedings-article"}],"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/W165654862","https://openalex.org/W619742285","https://openalex.org/W1515057696","https://openalex.org/W1576818901","https://openalex.org/W1584213932","https://openalex.org/W1591645366","https://openalex.org/W1604092088","https://openalex.org/W1900473378","https://openalex.org/W1980238966","https://openalex.org/W1989101984","https://openalex.org/W1989206164","https://openalex.org/W2018170331","https://openalex.org/W2021837985","https://openalex.org/W2023131636","https://openalex.org/W2052153221","https://openalex.org/W2078120153","https://openalex.org/W2103931815","https://openalex.org/W2134367663","https://openalex.org/W2137261852","https://openalex.org/W2147234763","https://openalex.org/W2149249560","https://openalex.org/W2154369084","https://openalex.org/W2169937856","https://openalex.org/W2493256084","https://openalex.org/W2911740249","https://openalex.org/W3150462322","https://openalex.org/W6663399104"],"related_works":["https://openalex.org/W2010370304","https://openalex.org/W2162083125","https://openalex.org/W1483596504","https://openalex.org/W2009506202","https://openalex.org/W2125266525","https://openalex.org/W2888937984","https://openalex.org/W2407804800","https://openalex.org/W2128012032","https://openalex.org/W2149131139","https://openalex.org/W108062576"],"abstract_inverted_index":{"XCS":[0,19,162],"is":[1,20,104],"a":[2,12,15,23,29,35,51,62],"learning":[3],"classifier":[4,16,63,84,128,166,185,192],"system":[5],"that":[6,205],"uses":[7],"accuracy-based":[8],"fitness":[9],"to":[10,94,105,115],"learn":[11],"problem.":[13],"Commonly,":[14],"rule":[17,92],"in":[18,61,71,79,120,135,187,214],"encoded":[21],"using":[22,111],"ternary":[24],"alphabet":[25],"based":[26,38,153,168,194],"condition":[27,81,125,167,193],"and":[28,90,147,170,183],"numeric":[30,46],"action.":[31],"Previously,":[32],"we":[33],"implemented":[34],"code-fragment":[36],"action":[37,47,59,118],"XCS,":[39],"called":[40],"XCSCFA,":[41,57,121],"where":[42],"the":[43,58,68,72,75,80,83,112,117,124,127,173,188,197,201,211],"typically":[44],"used":[45],"was":[48,64],"replaced":[49],"by":[50,66],"genetic":[52],"programming":[53],"like":[54],"tree-expression.":[55],"In":[56,177],"value":[60,119],"computed":[65],"loading":[67],"terminal":[69],"symbols":[70],"action-tree":[73],"with":[74],"corresponding":[76],"binary":[77],"values":[78],"of":[82,101,123,126,199],"rule.":[85,129],"This":[86],"enabled":[87],"accurate,":[88],"general":[89,182],"compact":[91,184],"sets":[93],"be":[95,133],"simply":[96],"produced.":[97],"The":[98,130,150],"main":[99],"contribution":[100],"this":[102],"work":[103],"investigate":[106],"an":[107],"intuitive":[108],"way,":[109],"i.e.":[110,141],"environmental":[113,151],"instance,":[114],"compute":[116],"instead":[122],"methods":[131],"will":[132],"compared":[134],"five":[136],"different":[137],"Boolean":[138],"problem":[139],"domains,":[140],"multiplexer,":[142],"even-parity,":[143],"majority-on,":[144],"design":[145],"verification,":[146],"carry":[148],"problems.":[149],"instance":[152],"XCSCFA":[154,169,195],"approach":[155],"had":[156],"better":[157],"classification":[158],"performance":[159],"than":[160],"standard":[161],"as":[163,165],"well":[164],"solved":[171],"all":[172],"problems":[174],"experimented":[175],"here.":[176],"addition":[178],"it":[179],"produced":[180],"more":[181],"rules":[186],"final":[189],"solution.":[190],"However,":[191],"has":[196],"advantage":[198],"producing":[200],"optimal":[202],"classifiers":[203],"such":[204],"they":[206],"are":[207],"clearly":[208],"separated":[209],"from":[210],"sub-optimal":[212],"ones":[213],"certain":[215],"domains.":[216]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2017,"cited_by_count":2},{"year":2016,"cited_by_count":1},{"year":2014,"cited_by_count":1},{"year":2013,"cited_by_count":2}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}
