{"id":"https://openalex.org/W2415155889","doi":"https://doi.org/10.1109/icra.2016.7487273","title":"Evolutionary optimization for parameterized whole-body dynamic motor skills","display_name":"Evolutionary optimization for parameterized whole-body dynamic motor skills","publication_year":2016,"publication_date":"2016-05-01","ids":{"openalex":"https://openalex.org/W2415155889","doi":"https://doi.org/10.1109/icra.2016.7487273","mag":"2415155889"},"language":"en","primary_location":{"id":"doi:10.1109/icra.2016.7487273","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icra.2016.7487273","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2016 IEEE International Conference on Robotics and Automation (ICRA)","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/A5064581452","display_name":"Sehoon Ha","orcid":"https://orcid.org/0000-0002-1972-328X"},"institutions":[{"id":"https://openalex.org/I130701444","display_name":"Georgia Institute of Technology","ror":"https://ror.org/01zkghx44","country_code":"US","type":"education","lineage":["https://openalex.org/I130701444"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Sehoon Ha","raw_affiliation_strings":["Department of Computer Science, Georgia Institute of Technology, GA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Computer Science, Georgia Institute of Technology, GA","institution_ids":["https://openalex.org/I130701444"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5048338914","display_name":"C. Karen Liu","orcid":"https://orcid.org/0000-0001-5926-0905"},"institutions":[{"id":"https://openalex.org/I130701444","display_name":"Georgia Institute of Technology","ror":"https://ror.org/01zkghx44","country_code":"US","type":"education","lineage":["https://openalex.org/I130701444"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"C. Karen Liu","raw_affiliation_strings":["Department of Computer Science, Georgia Institute of Technology, GA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Computer Science, Georgia Institute of Technology, GA","institution_ids":["https://openalex.org/I130701444"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I130701444"],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":11,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1390","last_page":"1397"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10462","display_name":"Reinforcement Learning in Robotics","score":0.9973999857902527,"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":0.9973999857902527,"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/T10653","display_name":"Robot Manipulation and Learning","score":0.996999979019165,"subfield":{"id":"https://openalex.org/subfields/2207","display_name":"Control and Systems 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/T10879","display_name":"Robotic Locomotion and Control","score":0.9965999722480774,"subfield":{"id":"https://openalex.org/subfields/2204","display_name":"Biomedical Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/parameterized-complexity","display_name":"Parameterized complexity","score":0.8770860433578491},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6955367922782898},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.6325927376747131},{"id":"https://openalex.org/keywords/range","display_name":"Range (aeronautics)","score":0.6126944422721863},{"id":"https://openalex.org/keywords/optimization-problem","display_name":"Optimization problem","score":0.5559591054916382},{"id":"https://openalex.org/keywords/mathematical-optimization","display_name":"Mathematical optimization","score":0.509159505367279},{"id":"https://openalex.org/keywords/robot","display_name":"Robot","score":0.49654752016067505},{"id":"https://openalex.org/keywords/exploit","display_name":"Exploit","score":0.49049919843673706},{"id":"https://openalex.org/keywords/evolutionary-algorithm","display_name":"Evolutionary algorithm","score":0.47106096148490906},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4159572422504425},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.36114054918289185},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.22985225915908813},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.18383058905601501},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.09376546740531921}],"concepts":[{"id":"https://openalex.org/C165464430","wikidata":"https://www.wikidata.org/wiki/Q1570441","display_name":"Parameterized complexity","level":2,"score":0.8770860433578491},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6955367922782898},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.6325927376747131},{"id":"https://openalex.org/C204323151","wikidata":"https://www.wikidata.org/wiki/Q905424","display_name":"Range (aeronautics)","level":2,"score":0.6126944422721863},{"id":"https://openalex.org/C137836250","wikidata":"https://www.wikidata.org/wiki/Q984063","display_name":"Optimization problem","level":2,"score":0.5559591054916382},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.509159505367279},{"id":"https://openalex.org/C90509273","wikidata":"https://www.wikidata.org/wiki/Q11012","display_name":"Robot","level":2,"score":0.49654752016067505},{"id":"https://openalex.org/C165696696","wikidata":"https://www.wikidata.org/wiki/Q11287","display_name":"Exploit","level":2,"score":0.49049919843673706},{"id":"https://openalex.org/C159149176","wikidata":"https://www.wikidata.org/wiki/Q14489129","display_name":"Evolutionary algorithm","level":2,"score":0.47106096148490906},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4159572422504425},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.36114054918289185},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.22985225915908813},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.18383058905601501},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.09376546740531921},{"id":"https://openalex.org/C146978453","wikidata":"https://www.wikidata.org/wiki/Q3798668","display_name":"Aerospace engineering","level":1,"score":0.0},{"id":"https://openalex.org/C201995342","wikidata":"https://www.wikidata.org/wiki/Q682496","display_name":"Systems engineering","level":1,"score":0.0},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icra.2016.7487273","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icra.2016.7487273","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2016 IEEE International Conference on Robotics and Automation (ICRA)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.4699999988079071,"display_name":"Quality Education","id":"https://metadata.un.org/sdg/4"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":31,"referenced_works":["https://openalex.org/W1929309940","https://openalex.org/W1976536305","https://openalex.org/W1993309788","https://openalex.org/W2007813200","https://openalex.org/W2037277559","https://openalex.org/W2050079439","https://openalex.org/W2069324174","https://openalex.org/W2100168570","https://openalex.org/W2116226448","https://openalex.org/W2120742447","https://openalex.org/W2122179812","https://openalex.org/W2123967136","https://openalex.org/W2133220762","https://openalex.org/W2133853511","https://openalex.org/W2138537392","https://openalex.org/W2140135625","https://openalex.org/W2141735805","https://openalex.org/W2144576818","https://openalex.org/W2149860990","https://openalex.org/W2156779957","https://openalex.org/W2202405398","https://openalex.org/W2512432267","https://openalex.org/W2591436094","https://openalex.org/W4242577313","https://openalex.org/W4256615025","https://openalex.org/W4285719527","https://openalex.org/W4300982816","https://openalex.org/W6675151561","https://openalex.org/W6678157427","https://openalex.org/W6680657880","https://openalex.org/W6688150747"],"related_works":["https://openalex.org/W17155033","https://openalex.org/W2051058708","https://openalex.org/W3207760230","https://openalex.org/W1496222301","https://openalex.org/W4312814274","https://openalex.org/W1590307681","https://openalex.org/W2536018345","https://openalex.org/W4285370786","https://openalex.org/W2296488620","https://openalex.org/W2022485595"],"abstract_inverted_index":{"Learning":[0],"a":[1,17,26,91,107,113,120,129,135,172],"parameterized":[2,78,136,173],"skill":[3,174],"is":[4,112,156],"essential":[5],"for":[6,19,76,90,139,175],"autonomous":[7],"robots":[8],"operating":[9],"in":[10,122,179],"an":[11,64,72],"unpredictable":[12],"environment.":[13],"Previous":[14],"techniques":[15,39],"learned":[16],"policy":[18,34,99,124],"each":[20,98,161],"example":[21],"task":[22,32],"individually":[23],"and":[24,33,62,145],"constructed":[25],"regression":[27],"model":[28],"to":[29,45,80,158,170],"map":[30],"between":[31],"parameter":[35,125],"spaces.":[36],"However,":[37],"these":[38],"have":[40],"less":[41],"success":[42],"when":[43],"applied":[44],"whole-body":[46,82],"dynamic":[47,83],"skills,":[48],"such":[49],"as":[50,106],"jumping":[51],"or":[52],"walking,":[53],"which":[54,133],"involve":[55],"the":[56,123,140,148,165,177,180],"challenges":[57],"of":[58,93,96,116,119,143,167,182],"handling":[59],"discrete":[60],"contacts":[61],"balancing":[63],"under-actuated":[65],"system":[66],"under":[67],"gravity.":[68],"This":[69],"paper":[70],"introduces":[71],"evolutionary":[73],"optimization":[74,109,131],"algorithm":[75,86,132,155],"learning":[77,97],"skills":[79],"achieve":[81],"tasks.":[84],"Our":[85,154],"simultaneously":[87],"learns":[88],"policies":[89],"range":[92,142,181],"tasks":[94,144,178],"instead":[95,118],"individually.":[100],"The":[101],"problem":[102],"can":[103],"be":[104],"formulated":[105],"nonconvex":[108],"whose":[110],"solution":[111],"closed":[114],"segment":[115],"curve":[117],"point":[121],"space.":[126],"We":[127],"develop":[128],"new":[130],"maintains":[134],"probability":[137],"distribution":[138,149],"entire":[141],"iteratively":[146],"updates":[147],"using":[150],"selected":[151],"elite":[152],"samples.":[153],"able":[157],"better":[159],"exploit":[160],"sample,":[162],"greatly":[163],"reducing":[164],"number":[166],"samples":[168],"required":[169],"optimize":[171],"all":[176],"interest.":[183]},"counts_by_year":[{"year":2019,"cited_by_count":7},{"year":2018,"cited_by_count":2},{"year":2017,"cited_by_count":1},{"year":2016,"cited_by_count":1}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}