{"id":"https://openalex.org/W2776365419","doi":"https://doi.org/10.1145/3205455.3205474","title":"ES is more than just a traditional finite-difference approximator","display_name":"ES is more than just a traditional finite-difference approximator","publication_year":2018,"publication_date":"2018-07-02","ids":{"openalex":"https://openalex.org/W2776365419","doi":"https://doi.org/10.1145/3205455.3205474","mag":"2776365419"},"language":"en","primary_location":{"id":"doi:10.1145/3205455.3205474","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3205455.3205474","pdf_url":"https://dl.acm.org/action/downloadSupplement?doi=10.1145%2F3205455.3205474&file=p450-lehman-suppl.pdf","source":{"id":"https://openalex.org/S4363608932","display_name":"Proceedings of the Genetic and Evolutionary Computation Conference","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","raw_type":"proceedings-article"},"type":"preprint","indexed_in":["arxiv","crossref","datacite"],"open_access":{"is_oa":true,"oa_status":"bronze","oa_url":"https://dl.acm.org/action/downloadSupplement?doi=10.1145%2F3205455.3205474&file=p450-lehman-suppl.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5053798319","display_name":"Joel Lehman","orcid":"https://orcid.org/0000-0002-9535-1123"},"institutions":[{"id":"https://openalex.org/I2946016260","display_name":"Uber AI (United States)","ror":"https://ror.org/05vm0ed18","country_code":"US","type":"company","lineage":["https://openalex.org/I2946016260"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Joel Lehman","raw_affiliation_strings":["Uber AI Labs"],"affiliations":[{"raw_affiliation_string":"Uber AI Labs","institution_ids":["https://openalex.org/I2946016260"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5105690544","display_name":"Jay Chen","orcid":null},"institutions":[{"id":"https://openalex.org/I2946016260","display_name":"Uber AI (United States)","ror":"https://ror.org/05vm0ed18","country_code":"US","type":"company","lineage":["https://openalex.org/I2946016260"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Jay Chen","raw_affiliation_strings":["Uber AI Labs"],"affiliations":[{"raw_affiliation_string":"Uber AI Labs","institution_ids":["https://openalex.org/I2946016260"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5112191507","display_name":"Jeff Clune","orcid":null},"institutions":[{"id":"https://openalex.org/I2946016260","display_name":"Uber AI (United States)","ror":"https://ror.org/05vm0ed18","country_code":"US","type":"company","lineage":["https://openalex.org/I2946016260"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Jeff Clune","raw_affiliation_strings":["Uber AI Labs"],"affiliations":[{"raw_affiliation_string":"Uber AI Labs","institution_ids":["https://openalex.org/I2946016260"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5029264794","display_name":"Kenneth O. Stanley","orcid":"https://orcid.org/0000-0003-4503-0839"},"institutions":[{"id":"https://openalex.org/I2946016260","display_name":"Uber AI (United States)","ror":"https://ror.org/05vm0ed18","country_code":"US","type":"company","lineage":["https://openalex.org/I2946016260"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Kenneth O. Stanley","raw_affiliation_strings":["Uber AI Labs"],"affiliations":[{"raw_affiliation_string":"Uber AI Labs","institution_ids":["https://openalex.org/I2946016260"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5053798319"],"corresponding_institution_ids":["https://openalex.org/I2946016260"],"apc_list":null,"apc_paid":null,"fwci":1.5924507,"has_fulltext":false,"cited_by_count":19,"citation_normalized_percentile":{"value":0.85205205,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"450","last_page":"457"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10462","display_name":"Reinforcement Learning in Robotics","score":0.9987999796867371,"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/T10462","display_name":"Reinforcement Learning in Robotics","score":0.9987999796867371,"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":0.9944999814033508,"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/T10174","display_name":"Animal Behavior and Reproduction","score":0.9753000140190125,"subfield":{"id":"https://openalex.org/subfields/1105","display_name":"Ecology, Evolution, Behavior and Systematics"},"field":{"id":"https://openalex.org/fields/11","display_name":"Agricultural and Biological Sciences"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.774516761302948},{"id":"https://openalex.org/keywords/reinforcement-learning","display_name":"Reinforcement learning","score":0.7106382846832275},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5729211568832397},{"id":"https://openalex.org/keywords/perturbation","display_name":"Perturbation (astronomy)","score":0.550855815410614},{"id":"https://openalex.org/keywords/gradient-descent","display_name":"Gradient descent","score":0.5365182757377625},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.49741557240486145},{"id":"https://openalex.org/keywords/population","display_name":"Population","score":0.44939476251602173},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.41697654128074646},{"id":"https://openalex.org/keywords/mathematical-optimization","display_name":"Mathematical optimization","score":0.3590555191040039},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.29488953948020935},{"id":"https://openalex.org/keywords/physics","display_name":"Physics","score":0.07878610491752625}],"concepts":[{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.774516761302948},{"id":"https://openalex.org/C97541855","wikidata":"https://www.wikidata.org/wiki/Q830687","display_name":"Reinforcement learning","level":2,"score":0.7106382846832275},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5729211568832397},{"id":"https://openalex.org/C177918212","wikidata":"https://www.wikidata.org/wiki/Q803623","display_name":"Perturbation (astronomy)","level":2,"score":0.550855815410614},{"id":"https://openalex.org/C153258448","wikidata":"https://www.wikidata.org/wiki/Q1199743","display_name":"Gradient descent","level":3,"score":0.5365182757377625},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.49741557240486145},{"id":"https://openalex.org/C2908647359","wikidata":"https://www.wikidata.org/wiki/Q2625603","display_name":"Population","level":2,"score":0.44939476251602173},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.41697654128074646},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.3590555191040039},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.29488953948020935},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.07878610491752625},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"id":"https://openalex.org/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","level":1,"score":0.0},{"id":"https://openalex.org/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"score":0.0},{"id":"https://openalex.org/C149923435","wikidata":"https://www.wikidata.org/wiki/Q37732","display_name":"Demography","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/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0}],"mesh":[],"locations_count":4,"locations":[{"id":"doi:10.1145/3205455.3205474","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3205455.3205474","pdf_url":"https://dl.acm.org/action/downloadSupplement?doi=10.1145%2F3205455.3205474&file=p450-lehman-suppl.pdf","source":{"id":"https://openalex.org/S4363608932","display_name":"Proceedings of the Genetic and Evolutionary Computation Conference","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","raw_type":"proceedings-article"},{"id":"pmh:oai:arXiv.org:1712.06568","is_oa":true,"landing_page_url":"http://arxiv.org/abs/1712.06568","pdf_url":"https://arxiv.org/pdf/1712.06568","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":"","raw_type":"text"},{"id":"mag:2776365419","is_oa":true,"landing_page_url":"http://export.arxiv.org/pdf/1712.06568","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":"doi:10.48550/arxiv.1712.06568","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.1712.06568","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:10.1145/3205455.3205474","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3205455.3205474","pdf_url":"https://dl.acm.org/action/downloadSupplement?doi=10.1145%2F3205455.3205474&file=p450-lehman-suppl.pdf","source":{"id":"https://openalex.org/S4363608932","display_name":"Proceedings of the Genetic and Evolutionary Computation Conference","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","raw_type":"proceedings-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2776365419.pdf","grobid_xml":"https://content.openalex.org/works/W2776365419.grobid-xml"},"referenced_works_count":37,"referenced_works":["https://openalex.org/W206440355","https://openalex.org/W1533846319","https://openalex.org/W1565012712","https://openalex.org/W1576660662","https://openalex.org/W1980266375","https://openalex.org/W1983153145","https://openalex.org/W2006036383","https://openalex.org/W2007705219","https://openalex.org/W2022730625","https://openalex.org/W2087617385","https://openalex.org/W2096368961","https://openalex.org/W2101822116","https://openalex.org/W2105557836","https://openalex.org/W2119717200","https://openalex.org/W2124289529","https://openalex.org/W2137104525","https://openalex.org/W2151083897","https://openalex.org/W2151965738","https://openalex.org/W2157166695","https://openalex.org/W2158782408","https://openalex.org/W2167433878","https://openalex.org/W2403330319","https://openalex.org/W2462548332","https://openalex.org/W2563259103","https://openalex.org/W2596367596","https://openalex.org/W2623491082","https://openalex.org/W2766302693","https://openalex.org/W2778749116","https://openalex.org/W2779171599","https://openalex.org/W2949608212","https://openalex.org/W2963790038","https://openalex.org/W3007384386","https://openalex.org/W3037207827","https://openalex.org/W4229809574","https://openalex.org/W4241088457","https://openalex.org/W6654985677","https://openalex.org/W6780559895"],"related_works":["https://openalex.org/W2596367596","https://openalex.org/W2963157343","https://openalex.org/W2778749116","https://openalex.org/W2949608212","https://openalex.org/W2173248099","https://openalex.org/W2166160300","https://openalex.org/W2151083897","https://openalex.org/W2145339207","https://openalex.org/W1522301498","https://openalex.org/W3008317338","https://openalex.org/W2963790038","https://openalex.org/W2779171599","https://openalex.org/W2623491082","https://openalex.org/W2342662072","https://openalex.org/W2085627234","https://openalex.org/W1588577808","https://openalex.org/W2915060045","https://openalex.org/W2950989964","https://openalex.org/W3152815381","https://openalex.org/W2563217198"],"abstract_inverted_index":{"An":[0],"evolution":[1,12],"strategy":[2,13],"(ES)":[3],"variant":[4],"based":[5],"on":[6],"a":[7,10,58,78],"simplification":[8],"of":[9,41,52,62,90,110,168],"natural":[11],"recently":[14],"attracted":[15],"attention":[16],"because":[17],"it":[18,56,66],"performs":[19],"surprisingly":[20],"well":[21],"in":[22,48,137],"challenging":[23],"deep":[24],"reinforcement":[25,149],"learning":[26,150],"domains.":[27,139],"It":[28,84],"searches":[29],"for":[30,77,86,133],"neural":[31],"network":[32],"parameters":[33,96],"by":[34],"generating":[35],"perturbations":[36],"to":[37,100,115,121,155,175,183],"the":[38,49,63,87,91,111,162,166],"current":[39],"set":[40],"parameters,":[42],"checking":[43],"their":[44,188],"performance,":[45],"and":[46,118,130,171,187],"moving":[47],"aggregate":[50],"direction":[51],"higher":[53],"reward.":[54],"Because":[55],"resembles":[57],"traditional":[59],"finite-difference":[60],"approximation":[61],"reward":[64,89],"gradient,":[65],"can":[67,104],"naturally":[68],"be":[69],"confused":[70],"with":[71,123],"one.":[72],"However,":[73],"this":[74,178],"ES":[75,106],"optimizes":[76,85],"different":[79],"gradient":[80,116],"than":[81,158],"just":[82],"reward:":[83],"average":[88],"entire":[92],"population,":[93],"thereby":[94],"seeking":[95],"that":[97],"are":[98,135,151],"robust":[99,154],"perturbation.":[101],"This":[102,126],"difference":[103],"channel":[105],"into":[107],"distinct":[108,124],"areas":[109],"search":[112],"space":[113],"relative":[114],"descent,":[117],"also":[119],"consequently":[120],"networks":[122,145],"properties.":[125],"unique":[127],"robustness-seeking":[128,172],"property,":[129],"its":[131],"consequences":[132],"optimization,":[134],"demonstrated":[136],"several":[138],"They":[140],"include":[141],"humanoid":[142],"locomotion,":[143],"where":[144],"from":[146],"policy":[147],"gradient-based":[148],"significantly":[152],"less":[153],"parameter":[156],"perturbation":[157],"ES-based":[159],"policies":[160],"solving":[161],"same":[163],"task.":[164],"While":[165],"implications":[167],"such":[169,185],"robustness":[170],"remain":[173],"open":[174],"further":[176],"study,":[177],"work's":[179],"main":[180],"contribution":[181],"is":[182],"highlight":[184],"differences":[186],"potential":[189],"importance.":[190]},"counts_by_year":[{"year":2024,"cited_by_count":1},{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":1},{"year":2019,"cited_by_count":4},{"year":2018,"cited_by_count":10},{"year":2017,"cited_by_count":2}],"updated_date":"2026-02-09T09:26:11.010843","created_date":"2025-10-10T00:00:00"}