{"id":"https://openalex.org/W2038817321","doi":"https://doi.org/10.1109/ijcnn.2014.6889701","title":"WWN: Integration with coarse-to-fine, supervised and reinforcement learning","display_name":"WWN: Integration with coarse-to-fine, supervised and reinforcement learning","publication_year":2014,"publication_date":"2014-07-01","ids":{"openalex":"https://openalex.org/W2038817321","doi":"https://doi.org/10.1109/ijcnn.2014.6889701","mag":"2038817321"},"language":"en","primary_location":{"id":"doi:10.1109/ijcnn.2014.6889701","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn.2014.6889701","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2014 International Joint Conference on Neural Networks (IJCNN)","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/A5031713387","display_name":"Zejia Zheng","orcid":"https://orcid.org/0000-0002-6527-6003"},"institutions":[{"id":"https://openalex.org/I87216513","display_name":"Michigan State University","ror":"https://ror.org/05hs6h993","country_code":"US","type":"education","lineage":["https://openalex.org/I87216513"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Zejia Zheng","raw_affiliation_strings":["Michigan State University, East Lansing, MI, USA","Michigan State University,East Lansing, MI, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Michigan State University, East Lansing, MI, USA","institution_ids":["https://openalex.org/I87216513"]},{"raw_affiliation_string":"Michigan State University,East Lansing, MI, USA","institution_ids":["https://openalex.org/I87216513"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102851268","display_name":"Juyang Weng","orcid":"https://orcid.org/0000-0003-1383-3872"},"institutions":[{"id":"https://openalex.org/I87216513","display_name":"Michigan State University","ror":"https://ror.org/05hs6h993","country_code":"US","type":"education","lineage":["https://openalex.org/I87216513"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Juyang Weng","raw_affiliation_strings":["Michigan State University, East Lansing, MI, USA","Michigan State University,East Lansing, MI, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Michigan State University, East Lansing, MI, USA","institution_ids":["https://openalex.org/I87216513"]},{"raw_affiliation_string":"Michigan State University,East Lansing, MI, USA","institution_ids":["https://openalex.org/I87216513"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5058849717","display_name":"Zhengyou Zhang","orcid":"https://orcid.org/0000-0002-6606-2525"},"institutions":[{"id":"https://openalex.org/I1290206253","display_name":"Microsoft (United States)","ror":"https://ror.org/00d0nc645","country_code":"US","type":"company","lineage":["https://openalex.org/I1290206253"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Zhengyou Zhang","raw_affiliation_strings":["Microsoft Research, Redmond, WA, USA","Mcrosoft Res., Redmond, WA, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Microsoft Research, Redmond, WA, USA","institution_ids":["https://openalex.org/I1290206253"]},{"raw_affiliation_string":"Mcrosoft Res., Redmond, WA, USA","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":5,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":"60","issue":null,"first_page":"1517","last_page":"1524"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10462","display_name":"Reinforcement Learning in Robotics","score":0.9952999949455261,"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":0.9952999949455261,"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/T12784","display_name":"Modular Robots and Swarm Intelligence","score":0.9904000163078308,"subfield":{"id":"https://openalex.org/subfields/2210","display_name":"Mechanical 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/T10789","display_name":"Interactive and Immersive Displays","score":0.9614999890327454,"subfield":{"id":"https://openalex.org/subfields/1709","display_name":"Human-Computer Interaction"},"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/reinforcement-learning","display_name":"Reinforcement learning","score":0.8619953393936157},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6874990463256836},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5542428493499756},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.5199912190437317},{"id":"https://openalex.org/keywords/object","display_name":"Object (grammar)","score":0.5136470198631287},{"id":"https://openalex.org/keywords/proactive-learning","display_name":"Proactive learning","score":0.4473534822463989},{"id":"https://openalex.org/keywords/reinforcement","display_name":"Reinforcement","score":0.43325960636138916},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.41537144780158997},{"id":"https://openalex.org/keywords/human\u2013computer-interaction","display_name":"Human\u2013computer interaction","score":0.3242047131061554},{"id":"https://openalex.org/keywords/robot-learning","display_name":"Robot learning","score":0.2810397446155548},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.09835821390151978}],"concepts":[{"id":"https://openalex.org/C97541855","wikidata":"https://www.wikidata.org/wiki/Q830687","display_name":"Reinforcement learning","level":2,"score":0.8619953393936157},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6874990463256836},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5542428493499756},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.5199912190437317},{"id":"https://openalex.org/C2781238097","wikidata":"https://www.wikidata.org/wiki/Q175026","display_name":"Object (grammar)","level":2,"score":0.5136470198631287},{"id":"https://openalex.org/C12298181","wikidata":"https://www.wikidata.org/wiki/Q7246814","display_name":"Proactive learning","level":5,"score":0.4473534822463989},{"id":"https://openalex.org/C67203356","wikidata":"https://www.wikidata.org/wiki/Q1321905","display_name":"Reinforcement","level":2,"score":0.43325960636138916},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.41537144780158997},{"id":"https://openalex.org/C107457646","wikidata":"https://www.wikidata.org/wiki/Q207434","display_name":"Human\u2013computer interaction","level":1,"score":0.3242047131061554},{"id":"https://openalex.org/C188888258","wikidata":"https://www.wikidata.org/wiki/Q7353390","display_name":"Robot learning","level":4,"score":0.2810397446155548},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.09835821390151978},{"id":"https://openalex.org/C66938386","wikidata":"https://www.wikidata.org/wiki/Q633538","display_name":"Structural engineering","level":1,"score":0.0},{"id":"https://openalex.org/C90509273","wikidata":"https://www.wikidata.org/wiki/Q11012","display_name":"Robot","level":2,"score":0.0},{"id":"https://openalex.org/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","level":1,"score":0.0},{"id":"https://openalex.org/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","level":0,"score":0.0},{"id":"https://openalex.org/C19966478","wikidata":"https://www.wikidata.org/wiki/Q4810574","display_name":"Mobile robot","level":3,"score":0.0},{"id":"https://openalex.org/C94625758","wikidata":"https://www.wikidata.org/wiki/Q7163","display_name":"Politics","level":2,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/ijcnn.2014.6889701","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn.2014.6889701","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2014 International Joint Conference on Neural Networks (IJCNN)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":19,"referenced_works":["https://openalex.org/W124618424","https://openalex.org/W161813247","https://openalex.org/W1622701847","https://openalex.org/W1967085570","https://openalex.org/W1969105566","https://openalex.org/W2023615316","https://openalex.org/W2024530670","https://openalex.org/W2096687174","https://openalex.org/W2130690456","https://openalex.org/W2148243231","https://openalex.org/W2151834591","https://openalex.org/W2151908411","https://openalex.org/W2163362738","https://openalex.org/W2165626265","https://openalex.org/W2170936849","https://openalex.org/W2334999485","https://openalex.org/W2493514692","https://openalex.org/W6604969303","https://openalex.org/W6723650072"],"related_works":["https://openalex.org/W4310083477","https://openalex.org/W2328553770","https://openalex.org/W2920061524","https://openalex.org/W1977959518","https://openalex.org/W2038908348","https://openalex.org/W2107890255","https://openalex.org/W2106552856","https://openalex.org/W2145821588","https://openalex.org/W2086122291","https://openalex.org/W1834370135"],"abstract_inverted_index":{"The":[0],"cost":[1,13],"of":[2,30,59,107,157,175,230],"autonomous":[3],"development":[4],"is":[5,10,17,44,49,143,160,168,182],"substantial.":[6],"Although":[7],"supervised":[8,52,108],"learning":[9,26,43,62,109,112,211],"effective,":[11],"the":[12,68,78,134,141,151,155,164,173,180,186],"demand":[14],"on":[15,82,86,122],"teachers":[16],"often":[18],"too":[19],"high":[20],"to":[21,34,132,146,153,190,199],"be":[22],"constantly":[23],"applied.":[24],"Reinforcement":[25],"can":[27],"take":[28],"advantage":[29],"physical":[31,165],"reality":[32],"due":[33],"environmental":[35],"feedback":[36],"and":[37,57,94,103,110,136,215,220,223],"inspections.":[38],"Information":[39],"required":[40,50],"in":[41,51,67,77,113,140,196,207],"reinforcement":[42,111,123],"not":[45,144],"as":[46,48],"specific":[47],"learning.":[53],"Integration":[54],"theories,":[55],"methods,":[56],"analysis":[58,104],"these":[60],"two":[61],"strategies":[63],"are":[64,217],"still":[65],"rare":[66],"literature":[69],"although":[70],"such":[71],"integration":[72,106,142],"has":[73],"been":[74],"well":[75],"known":[76,120],"animal":[79],"kingdom.":[80],"Based":[81],"our":[83,100,178,204],"prior":[84],"work":[85,121,206],"a":[87,148,197,208],"general":[88],"purpose":[89],"framework":[90,127],"called":[91],"Developmental":[92],"Network":[93],"its":[95],"embodiment":[96],"Where-What-Network,":[97],"we":[98],"present":[99],"theory,":[101],"method,":[102],"for":[105,150],"this":[114,125],"paper.":[115],"Different":[116],"from":[117,226],"all":[118],"other":[119],"learning,":[124,158],"DN":[126],"uses":[128],"fully":[129],"emergent":[130],"representation":[131,193],"avoid":[133],"brittleness":[135],"task-specific":[137],"representations.":[138],"Central":[139],"just":[145],"provide":[147],"freedom":[149],"teacher":[152],"choose":[154],"mode":[156],"which":[159],"necessary":[161],"especially":[162],"when":[163],"non-living":[166],"world":[167],"an":[169],"implicit":[170],"teacher,":[171],"but":[172],"mechanism":[174],"scaffolding.":[176],"In":[177],"experiment":[179],"scaffolding":[181],"reflected":[183],"by":[184],"allowing":[185],"location":[187,222],"motor(LM)":[188],"neurons":[189],"gradually":[191],"refine":[192],"through":[194],"splitting(mitosis)":[195],"coarse":[198],"fine":[200],"scheme.":[201],"We":[202],"report":[203],"experimental":[205],"very":[209],"challenging":[210],"setting:":[212],"both":[213],"object":[214],"backgrounds":[216],"unknown(cluttered":[218],"settings)":[219],"concepts(e.g.":[221],"type)":[224],"emerge":[225],"agent-environment":[227],"interactions,":[228],"instead":[229],"rigidly":[231],"handcrafted.":[232]},"counts_by_year":[{"year":2021,"cited_by_count":1},{"year":2015,"cited_by_count":3},{"year":2014,"cited_by_count":1}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}
