{"id":"https://openalex.org/W3210013777","doi":"https://doi.org/10.1109/tnnls.2021.3121432","title":"Exploration With Task Information for Meta Reinforcement Learning","display_name":"Exploration With Task Information for Meta Reinforcement Learning","publication_year":2021,"publication_date":"2021-11-05","ids":{"openalex":"https://openalex.org/W3210013777","doi":"https://doi.org/10.1109/tnnls.2021.3121432","mag":"3210013777","pmid":"https://pubmed.ncbi.nlm.nih.gov/34739382"},"language":"en","primary_location":{"id":"doi:10.1109/tnnls.2021.3121432","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tnnls.2021.3121432","pdf_url":null,"source":{"id":"https://openalex.org/S4210175523","display_name":"IEEE Transactions on Neural Networks and Learning Systems","issn_l":"2162-237X","issn":["2162-237X","2162-2388"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Neural Networks and Learning Systems","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","pubmed"],"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/A5101405955","display_name":"Peng Jiang","orcid":"https://orcid.org/0000-0001-8133-5010"},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Peng Jiang","raw_affiliation_strings":["Department of Automation, Tsinghua University, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0001-8133-5010","affiliations":[{"raw_affiliation_string":"Department of Automation, Tsinghua University, Beijing, China","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5068624597","display_name":"Shiji Song","orcid":"https://orcid.org/0000-0001-7361-9283"},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shiji Song","raw_affiliation_strings":["Department of Automation, Tsinghua University, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0001-7361-9283","affiliations":[{"raw_affiliation_string":"Department of Automation, Tsinghua University, Beijing, China","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5013240918","display_name":"Gao Huang","orcid":"https://orcid.org/0000-0002-7251-0988"},"institutions":[{"id":"https://openalex.org/I4210100255","display_name":"Beijing Academy of Artificial Intelligence","ror":"https://ror.org/016a74861","country_code":"CN","type":"other","lineage":["https://openalex.org/I4210100255"]},{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Gao Huang","raw_affiliation_strings":["Department of Automation, Tsinghua University, Beijing, China","Beijing Academy of Artificial Intelligence, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0002-7251-0988","affiliations":[{"raw_affiliation_string":"Department of Automation, Tsinghua University, Beijing, China","institution_ids":["https://openalex.org/I99065089"]},{"raw_affiliation_string":"Beijing Academy of Artificial Intelligence, Beijing, China","institution_ids":["https://openalex.org/I4210100255"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.6997,"has_fulltext":false,"cited_by_count":8,"citation_normalized_percentile":{"value":0.7694054,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":97},"biblio":{"volume":"34","issue":"8","first_page":"4033","last_page":"4046"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10462","display_name":"Reinforcement Learning in Robotics","score":0.9997000098228455,"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":0.9997000098228455,"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/T10429","display_name":"EEG and Brain-Computer Interfaces","score":0.9848999977111816,"subfield":{"id":"https://openalex.org/subfields/2805","display_name":"Cognitive Neuroscience"},"field":{"id":"https://openalex.org/fields/28","display_name":"Neuroscience"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},{"id":"https://openalex.org/T10502","display_name":"Advanced Memory and Neural Computing","score":0.978600025177002,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8299821615219116},{"id":"https://openalex.org/keywords/reinforcement-learning","display_name":"Reinforcement learning","score":0.8199561238288879},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.615501880645752},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.6027952432632446},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.579974353313446},{"id":"https://openalex.org/keywords/meta-learning","display_name":"Meta learning (computer science)","score":0.5793825387954712},{"id":"https://openalex.org/keywords/context","display_name":"Context (archaeology)","score":0.5454753637313843},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.5451365113258362}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8299821615219116},{"id":"https://openalex.org/C97541855","wikidata":"https://www.wikidata.org/wiki/Q830687","display_name":"Reinforcement learning","level":2,"score":0.8199561238288879},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.615501880645752},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.6027952432632446},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.579974353313446},{"id":"https://openalex.org/C2781002164","wikidata":"https://www.wikidata.org/wiki/Q6822311","display_name":"Meta learning (computer science)","level":3,"score":0.5793825387954712},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.5454753637313843},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5451365113258362},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0},{"id":"https://openalex.org/C151730666","wikidata":"https://www.wikidata.org/wiki/Q7205","display_name":"Paleontology","level":1,"score":0.0},{"id":"https://openalex.org/C187736073","wikidata":"https://www.wikidata.org/wiki/Q2920921","display_name":"Management","level":1,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/tnnls.2021.3121432","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tnnls.2021.3121432","pdf_url":null,"source":{"id":"https://openalex.org/S4210175523","display_name":"IEEE Transactions on Neural Networks and Learning Systems","issn_l":"2162-237X","issn":["2162-237X","2162-2388"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Neural Networks and Learning Systems","raw_type":"journal-article"},{"id":"pmid:34739382","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/34739382","pdf_url":null,"source":{"id":"https://openalex.org/S4306525036","display_name":"PubMed","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE transactions on neural networks and learning systems","raw_type":null}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G4055798484","display_name":null,"funder_award_id":"61936009","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G6879802318","display_name":null,"funder_award_id":"61906106","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G8753403390","display_name":null,"funder_award_id":"62022048","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":50,"referenced_works":["https://openalex.org/W115285041","https://openalex.org/W2145339207","https://openalex.org/W2578206533","https://openalex.org/W2583993537","https://openalex.org/W2742093937","https://openalex.org/W2785397462","https://openalex.org/W2900582619","https://openalex.org/W2945020056","https://openalex.org/W2962937819","https://openalex.org/W2965140792","https://openalex.org/W2967727187","https://openalex.org/W2989966838","https://openalex.org/W3022124161","https://openalex.org/W3100944043","https://openalex.org/W3126935522","https://openalex.org/W3166906164","https://openalex.org/W3175662487","https://openalex.org/W4294646197","https://openalex.org/W4300971732","https://openalex.org/W6683204974","https://openalex.org/W6716474083","https://openalex.org/W6729433768","https://openalex.org/W6731982132","https://openalex.org/W6736057607","https://openalex.org/W6740879895","https://openalex.org/W6742288159","https://openalex.org/W6747473740","https://openalex.org/W6747625265","https://openalex.org/W6747943641","https://openalex.org/W6748576644","https://openalex.org/W6748600884","https://openalex.org/W6748839928","https://openalex.org/W6749922295","https://openalex.org/W6750254146","https://openalex.org/W6751813273","https://openalex.org/W6753803377","https://openalex.org/W6755476724","https://openalex.org/W6757021410","https://openalex.org/W6758714319","https://openalex.org/W6760698134","https://openalex.org/W6762959241","https://openalex.org/W6764724164","https://openalex.org/W6765145614","https://openalex.org/W6768560635","https://openalex.org/W6768602481","https://openalex.org/W6769596995","https://openalex.org/W6770048201","https://openalex.org/W6770190457","https://openalex.org/W6774268721","https://openalex.org/W6776731554"],"related_works":["https://openalex.org/W4362501864","https://openalex.org/W3130669838","https://openalex.org/W2785397462","https://openalex.org/W4294873804","https://openalex.org/W4383109125","https://openalex.org/W2091347716","https://openalex.org/W98577079","https://openalex.org/W2891227010","https://openalex.org/W4319309271","https://openalex.org/W2548988175"],"abstract_inverted_index":{"Meta":[0],"reinforcement":[1],"learning":[2,36],"(meta-RL)":[3],"is":[4,48],"a":[5,31,66,88],"promising":[6],"technique":[7],"for":[8,111],"fast":[9],"task":[10,39,42,46,103,116,130,157,160,179,220],"adaptation":[11],"by":[12,29],"leveraging":[13],"prior":[14],"knowledge":[15],"from":[16],"previous":[17],"tasks.":[18],"Recently,":[19],"context-based":[20,68,84],"meta-RL":[21,69,189],"has":[22],"been":[23],"proposed":[24],"to":[25,57,96,149],"improve":[26],"data":[27],"efficiency":[28,218],"applying":[30],"principled":[32],"framework,":[33],"dividing":[34],"the":[35,45,77,113,119,138,150,164,169,212],"procedure":[37,140],"into":[38,141],"inference":[40,158,180],"and":[41,80,102,144,159,162,178,197,219],"execution.":[43],"However,":[44],"information":[47,131],"not":[49],"adequately":[50],"leveraged":[51],"in":[52,83,100,132,168,214],"this":[53,62],"approach,":[54],"thus":[55],"leading":[56],"inefficient":[58],"exploration.":[59],"To":[60],"address":[61],"problem,":[63],"we":[64,86,173],"propose":[65,87],"novel":[67,89],"framework":[70],"with":[71,186,194],"an":[72],"improved":[73],"exploration":[74,79,94,99,134,143,146,171],"mechanism.":[75],"For":[76],"existing":[78],"execution":[81,161],"problem":[82],"meta-RL,":[85],"objective":[90],"that":[91,205],"employs":[92],"two":[93,170],"terms":[95,215],"encourage":[97],"better":[98],"action":[101,123,153],"embedding":[104],"space,":[105],"respectively.":[106],"The":[107,201],"first":[108],"term":[109],"pushes":[110],"improving":[112],"diversity":[114],"of":[115,152,216],"inference,":[117],"while":[118],"second":[120],"term,":[121],"named":[122],"information,":[124],"works":[125],"as":[126],"sharing":[127],"or":[128],"hiding":[129],"different":[133],"stages.":[135],"We":[136,182],"divide":[137],"meta-training":[139],"task-independent":[142],"task-relevant":[145],"stages":[147],"according":[148],"utilization":[151],"information.":[154],"By":[155],"decoupling":[156],"proposing":[163],"respective":[165],"optimization":[166],"objectives":[167],"stages,":[172],"can":[174],"efficiently":[175],"learn":[176],"policy":[177],"networks.":[181],"compare":[183],"our":[184,206],"algorithm":[185],"several":[187],"popular":[188],"methods":[190],"on":[191,211],"MuJoco":[192],"benchmarks":[193,213],"both":[195],"dense":[196],"sparse":[198],"reward":[199],"settings.":[200],"empirical":[202],"results":[203],"show":[204],"method":[207],"significantly":[208],"outperforms":[209],"baselines":[210],"sample":[217],"performance.":[221]},"counts_by_year":[{"year":2025,"cited_by_count":3},{"year":2024,"cited_by_count":3},{"year":2023,"cited_by_count":2}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}