{"id":"https://openalex.org/W3005882800","doi":"https://doi.org/10.1145/3377930.3390249","title":"XCS classifier system with experience replay","display_name":"XCS classifier system with experience replay","publication_year":2020,"publication_date":"2020-06-25","ids":{"openalex":"https://openalex.org/W3005882800","doi":"https://doi.org/10.1145/3377930.3390249","mag":"3005882800"},"language":"en","primary_location":{"id":"doi:10.1145/3377930.3390249","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3377930.3390249","pdf_url":"https://dl.acm.org/action/downloadSupplement?doi=10.1145%2F3377930.3390249&file=p404-stein-suppl.pdf","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2020 Genetic and Evolutionary Computation Conference","raw_type":"proceedings-article"},"type":"preprint","indexed_in":["arxiv","crossref","datacite"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://dl.acm.org/action/downloadSupplement?doi=10.1145%2F3377930.3390249&file=p404-stein-suppl.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5045271767","display_name":"Anthony Stein","orcid":"https://orcid.org/0000-0002-1808-9758"},"institutions":[{"id":"https://openalex.org/I110079840","display_name":"University of Hohenheim","ror":"https://ror.org/00b1c9541","country_code":"DE","type":"education","lineage":["https://openalex.org/I110079840"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Anthony Stein","raw_affiliation_strings":["University of Hohenheim, Germany"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Hohenheim, Germany","institution_ids":["https://openalex.org/I110079840"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5061441120","display_name":"Roland Maier","orcid":"https://orcid.org/0000-0001-7509-1590"},"institutions":[{"id":"https://openalex.org/I179225836","display_name":"University of Augsburg","ror":"https://ror.org/03p14d497","country_code":"DE","type":"education","lineage":["https://openalex.org/I179225836"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Roland Maier","raw_affiliation_strings":["University of Augsburg, Germany","Univ. of Augsburg (Germany)"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Augsburg, Germany","institution_ids":["https://openalex.org/I179225836"]},{"raw_affiliation_string":"Univ. of Augsburg (Germany)","institution_ids":["https://openalex.org/I179225836"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5009242098","display_name":"Lukas Rosenbauer","orcid":null},"institutions":[{"id":"https://openalex.org/I4210123307","display_name":"BSH Hausger\u00e4te (Germany)","ror":"https://ror.org/0231f9890","country_code":"DE","type":"company","lineage":["https://openalex.org/I4210123307","https://openalex.org/I889804353"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Lukas Rosenbauer","raw_affiliation_strings":["BSH Home Appliances, Germany"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"BSH Home Appliances, Germany","institution_ids":["https://openalex.org/I4210123307"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5035545860","display_name":"J\u00f6rg H\u00e4hner","orcid":"https://orcid.org/0000-0003-0107-264X"},"institutions":[{"id":"https://openalex.org/I179225836","display_name":"University of Augsburg","ror":"https://ror.org/03p14d497","country_code":"DE","type":"education","lineage":["https://openalex.org/I179225836"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"J\u00f6rg H\u00e4hner","raw_affiliation_strings":["University of Augsburg, Germany","Univ. of Augsburg (Germany)"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Augsburg, Germany","institution_ids":["https://openalex.org/I179225836"]},{"raw_affiliation_string":"Univ. of Augsburg (Germany)","institution_ids":["https://openalex.org/I179225836"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.1354,"has_fulltext":true,"cited_by_count":1,"citation_normalized_percentile":{"value":0.52695009,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":94},"biblio":{"volume":null,"issue":null,"first_page":"404","last_page":"413"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11975","display_name":"Evolutionary Algorithms and Applications","score":0.9980999827384949,"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":0.9980999827384949,"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/T10502","display_name":"Advanced Memory and Neural Computing","score":0.9883999824523926,"subfield":{"id":"https://openalex.org/subfields/2208","display_name":"Electrical and Electronic Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T12611","display_name":"Neural Networks and Reservoir Computing","score":0.9624000191688538,"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/leverage","display_name":"Leverage (statistics)","score":0.7626216411590576},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7520648241043091},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7415850162506104},{"id":"https://openalex.org/keywords/reinforcement-learning","display_name":"Reinforcement learning","score":0.716206967830658},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.6317023634910583},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.5812545418739319},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.5807593464851379},{"id":"https://openalex.org/keywords/deep-neural-networks","display_name":"Deep neural networks","score":0.42420676350593567}],"concepts":[{"id":"https://openalex.org/C153083717","wikidata":"https://www.wikidata.org/wiki/Q6535263","display_name":"Leverage (statistics)","level":2,"score":0.7626216411590576},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7520648241043091},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7415850162506104},{"id":"https://openalex.org/C97541855","wikidata":"https://www.wikidata.org/wiki/Q830687","display_name":"Reinforcement learning","level":2,"score":0.716206967830658},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.6317023634910583},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.5812545418739319},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.5807593464851379},{"id":"https://openalex.org/C2984842247","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep neural networks","level":3,"score":0.42420676350593567}],"mesh":[],"locations_count":5,"locations":[{"id":"doi:10.1145/3377930.3390249","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3377930.3390249","pdf_url":"https://dl.acm.org/action/downloadSupplement?doi=10.1145%2F3377930.3390249&file=p404-stein-suppl.pdf","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2020 Genetic and Evolutionary Computation Conference","raw_type":"proceedings-article"},{"id":"pmh:oai:arXiv.org:2002.05628","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2002.05628","pdf_url":"https://arxiv.org/pdf/2002.05628","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},{"id":"mag:3005882800","is_oa":true,"landing_page_url":"http://arxiv.org/pdf/2002.05628.pdf","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"arXiv (Cornell University)","raw_type":null},{"id":"pmh:oai:uni-augsburg.opus-bayern.de:83051","is_oa":false,"landing_page_url":"https://opus.bibliothek.uni-augsburg.de/opus4/frontdoor/index/index/docId/83051","pdf_url":null,"source":{"id":"https://openalex.org/S4306400930","display_name":"OPUS (Augsburg University)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I119916105","host_organization_name":"Augsburg University","host_organization_lineage":["https://openalex.org/I119916105"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"bookpart"},{"id":"doi:10.48550/arxiv.2002.05628","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2002.05628","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"article"}],"best_oa_location":{"id":"doi:10.1145/3377930.3390249","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3377930.3390249","pdf_url":"https://dl.acm.org/action/downloadSupplement?doi=10.1145%2F3377930.3390249&file=p404-stein-suppl.pdf","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2020 Genetic and Evolutionary Computation Conference","raw_type":"proceedings-article"},"sustainable_development_goals":[{"display_name":"Peace, Justice and strong institutions","id":"https://metadata.un.org/sdg/16","score":0.75}],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W3005882800.pdf","grobid_xml":"https://content.openalex.org/works/W3005882800.grobid-xml"},"referenced_works_count":54,"referenced_works":["https://openalex.org/W30810292","https://openalex.org/W162220251","https://openalex.org/W1542723682","https://openalex.org/W1548227173","https://openalex.org/W1569849952","https://openalex.org/W1573351619","https://openalex.org/W1582436621","https://openalex.org/W1585023907","https://openalex.org/W1612687168","https://openalex.org/W1757796397","https://openalex.org/W1979602772","https://openalex.org/W1980035368","https://openalex.org/W1989101984","https://openalex.org/W1996833561","https://openalex.org/W1999128321","https://openalex.org/W2000659199","https://openalex.org/W2045761815","https://openalex.org/W2052153221","https://openalex.org/W2057951681","https://openalex.org/W2064957497","https://openalex.org/W2073677619","https://openalex.org/W2084028892","https://openalex.org/W2098888151","https://openalex.org/W2105709189","https://openalex.org/W2125321720","https://openalex.org/W2137261852","https://openalex.org/W2139418546","https://openalex.org/W2141559645","https://openalex.org/W2145339207","https://openalex.org/W2152615835","https://openalex.org/W2167814825","https://openalex.org/W2286297822","https://openalex.org/W2312609093","https://openalex.org/W2477329842","https://openalex.org/W2496413771","https://openalex.org/W2523152773","https://openalex.org/W2557835688","https://openalex.org/W2584068132","https://openalex.org/W2733988186","https://openalex.org/W2734584764","https://openalex.org/W2766447205","https://openalex.org/W2768898054","https://openalex.org/W2811092602","https://openalex.org/W2895774836","https://openalex.org/W2954032500","https://openalex.org/W2961727008","https://openalex.org/W2963477884","https://openalex.org/W2964001908","https://openalex.org/W2981658733","https://openalex.org/W2982316857","https://openalex.org/W3004580762","https://openalex.org/W3011120880","https://openalex.org/W3028232160","https://openalex.org/W3106070636"],"related_works":["https://openalex.org/W3039358545","https://openalex.org/W2922466935","https://openalex.org/W2994249964","https://openalex.org/W2982380123","https://openalex.org/W2925216817","https://openalex.org/W2890219357","https://openalex.org/W2971538581","https://openalex.org/W3206895853","https://openalex.org/W3102797050","https://openalex.org/W1480527676","https://openalex.org/W2898807633","https://openalex.org/W3020401063","https://openalex.org/W3131806378","https://openalex.org/W3034943389","https://openalex.org/W2142671416","https://openalex.org/W2554161793","https://openalex.org/W2521274174","https://openalex.org/W3010604601","https://openalex.org/W3132064648","https://openalex.org/W3041310931"],"abstract_inverted_index":{"XCS":[0,35,106,129,164],"constitutes":[1,84],"the":[2,45,52,74,87,91,100,125,148],"most":[3],"deeply":[4],"investigated":[5],"classifier":[6],"system":[7],"today.":[8],"It":[9],"offers":[10],"strong":[11,140],"potentials":[12],"and":[13,32],"comes":[14],"with":[15,130],"inherent":[16],"capabilities":[17],"for":[18,90,135,163,172],"mastering":[19],"a":[20,78],"variety":[21],"of":[22,47,86,99,110,127,144],"different":[23],"learning":[24],"tasks.":[25],"Besides":[26],"outstanding":[27],"successes":[28],"in":[29,40,51,142],"various":[30],"classification":[31],"regression":[33],"tasks,":[34],"also":[36],"proved":[37],"very":[38],"effective":[39],"certain":[41],"multi-step":[42],"environments":[43],"from":[44],"domain":[46],"reinforcement":[48],"learning.":[49],"Especially":[50],"latter":[53],"domain,":[54],"recent":[55],"advances":[56],"have":[57],"been":[58],"mainly":[59],"driven":[60],"by":[61],"algorithms":[62],"which":[63,73],"model":[64],"their":[65],"policies":[66],"based":[67],"on":[68],"deep":[69],"neural":[70,101],"networks,":[71],"among":[72],"Deep-Q-Network":[75],"(DQN)":[76],"being":[77],"prominent":[79],"representative.":[80],"Experience":[81],"Replay":[82],"(ER)":[83],"one":[85],"crucial":[88],"factors":[89],"DQN's":[92],"successes,":[93],"since":[94],"it":[95],"facilitates":[96],"stabilized":[97],"training":[98],"network-based":[102],"Q-function":[103],"approximators.":[104],"Surprisingly,":[105],"barely":[107],"takes":[108],"advantage":[109],"similar":[111],"mechanisms":[112],"that":[113,134,153],"leverage":[114],"remembered":[115],"raw":[116],"experiences.":[117],"To":[118],"bridge":[119],"this":[120,122],"gap,":[121],"paper":[123],"investigates":[124],"benefits":[126],"extending":[128],"ER.":[131],"We":[132],"demonstrate":[133],"single-step":[136],"tasks":[137],"ER":[138,154],"yields":[139],"improvements":[141],"terms":[143],"sample":[145],"efficiency.":[146],"On":[147],"downside,":[149],"however,":[150],"we":[151],"reveal":[152],"might":[155],"further":[156],"aggravate":[157],"well-studied":[158],"issues":[159],"not":[160],"yet":[161],"solved":[162],"when":[165],"applied":[166],"to":[167],"sequential":[168],"decision":[169],"problems":[170],"demanding":[171],"long-action-chains.":[173]},"counts_by_year":[{"year":2021,"cited_by_count":1}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}