{"id":"https://openalex.org/W4385834276","doi":"https://doi.org/10.1109/access.2023.3305453","title":"Generative Adversarial Inverse Reinforcement Learning With Deep Deterministic Policy Gradient","display_name":"Generative Adversarial Inverse Reinforcement Learning With Deep Deterministic Policy Gradient","publication_year":2023,"publication_date":"2023-01-01","ids":{"openalex":"https://openalex.org/W4385834276","doi":"https://doi.org/10.1109/access.2023.3305453"},"language":"en","primary_location":{"id":"doi:10.1109/access.2023.3305453","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2023.3305453","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/6514899/10217826.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"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 Access","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://ieeexplore.ieee.org/ielx7/6287639/6514899/10217826.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5102883267","display_name":"Ming Zhan","orcid":"https://orcid.org/0009-0002-1717-6013"},"institutions":[{"id":"https://openalex.org/I1456306","display_name":"North China University of Technology","ror":"https://ror.org/01nky7652","country_code":"CN","type":"education","lineage":["https://openalex.org/I1456306"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ming Zhan","raw_affiliation_strings":["School of Electrical and Control Engineering, North China University of Technology, Beijing, China"],"raw_orcid":"https://orcid.org/0009-0002-1717-6013","affiliations":[{"raw_affiliation_string":"School of Electrical and Control Engineering, North China University of Technology, Beijing, China","institution_ids":["https://openalex.org/I1456306"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101855222","display_name":"Jingjing Fan","orcid":"https://orcid.org/0000-0002-3203-311X"},"institutions":[{"id":"https://openalex.org/I1456306","display_name":"North China University of Technology","ror":"https://ror.org/01nky7652","country_code":"CN","type":"education","lineage":["https://openalex.org/I1456306"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jingjing Fan","raw_affiliation_strings":["Intelligent Transportation Key Laboratory, North China University of Technology, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0002-3203-311X","affiliations":[{"raw_affiliation_string":"Intelligent Transportation Key Laboratory, North China University of Technology, Beijing, China","institution_ids":["https://openalex.org/I1456306"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5102755970","display_name":"Jianying Guo","orcid":"https://orcid.org/0009-0006-3835-4535"},"institutions":[{"id":"https://openalex.org/I4210107650","display_name":"Tianjin Vocational Institute","ror":"https://ror.org/012tjde79","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210107650"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jianying Guo","raw_affiliation_strings":["Tianjin Vocational Institute, Tianjin, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Tianjin Vocational Institute, Tianjin, China","institution_ids":["https://openalex.org/I4210107650"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":{"value":1850,"currency":"USD","value_usd":1850},"apc_paid":{"value":1850,"currency":"USD","value_usd":1850},"fwci":0.6526,"has_fulltext":true,"cited_by_count":4,"citation_normalized_percentile":{"value":0.74959206,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":96},"biblio":{"volume":"11","issue":null,"first_page":"87732","last_page":"87746"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11689","display_name":"Adversarial Robustness in Machine Learning","score":0.9975000023841858,"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/T11689","display_name":"Adversarial Robustness in Machine Learning","score":0.9975000023841858,"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/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9945999979972839,"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/T11099","display_name":"Autonomous Vehicle Technology and Safety","score":0.9908999800682068,"subfield":{"id":"https://openalex.org/subfields/2203","display_name":"Automotive 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/adversarial-system","display_name":"Adversarial system","score":0.8462408781051636},{"id":"https://openalex.org/keywords/reinforcement-learning","display_name":"Reinforcement learning","score":0.7172387838363647},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6853681802749634},{"id":"https://openalex.org/keywords/generative-grammar","display_name":"Generative grammar","score":0.6459534764289856},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5898425579071045},{"id":"https://openalex.org/keywords/inverse","display_name":"Inverse","score":0.425849586725235},{"id":"https://openalex.org/keywords/inverse-problem","display_name":"Inverse problem","score":0.4233753979206085},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.1857510805130005}],"concepts":[{"id":"https://openalex.org/C37736160","wikidata":"https://www.wikidata.org/wiki/Q1801315","display_name":"Adversarial system","level":2,"score":0.8462408781051636},{"id":"https://openalex.org/C97541855","wikidata":"https://www.wikidata.org/wiki/Q830687","display_name":"Reinforcement learning","level":2,"score":0.7172387838363647},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6853681802749634},{"id":"https://openalex.org/C39890363","wikidata":"https://www.wikidata.org/wiki/Q36108","display_name":"Generative grammar","level":2,"score":0.6459534764289856},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5898425579071045},{"id":"https://openalex.org/C207467116","wikidata":"https://www.wikidata.org/wiki/Q4385666","display_name":"Inverse","level":2,"score":0.425849586725235},{"id":"https://openalex.org/C135252773","wikidata":"https://www.wikidata.org/wiki/Q1567213","display_name":"Inverse problem","level":2,"score":0.4233753979206085},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.1857510805130005},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/access.2023.3305453","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2023.3305453","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/6514899/10217826.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"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 Access","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:ac60ba85e9444282a8f4b5e5b608ec0c","is_oa":true,"landing_page_url":"https://doaj.org/article/ac60ba85e9444282a8f4b5e5b608ec0c","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","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":"repository"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"IEEE Access, Vol 11, Pp 87732-87746 (2023)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1109/access.2023.3305453","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2023.3305453","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/6514899/10217826.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"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 Access","raw_type":"journal-article"},"sustainable_development_goals":[{"display_name":"Peace, Justice and strong institutions","score":0.7200000286102295,"id":"https://metadata.un.org/sdg/16"}],"awards":[],"funders":[],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4385834276.pdf","grobid_xml":"https://content.openalex.org/works/W4385834276.grobid-xml"},"referenced_works_count":48,"referenced_works":["https://openalex.org/W1527702126","https://openalex.org/W2008491003","https://openalex.org/W2070469928","https://openalex.org/W2101786389","https://openalex.org/W2744369598","https://openalex.org/W2909906617","https://openalex.org/W2963508354","https://openalex.org/W2963730239","https://openalex.org/W2963864421","https://openalex.org/W2967762122","https://openalex.org/W2980001345","https://openalex.org/W2984045653","https://openalex.org/W3035574168","https://openalex.org/W3036472058","https://openalex.org/W3037606473","https://openalex.org/W3081441254","https://openalex.org/W3096831136","https://openalex.org/W3107293915","https://openalex.org/W3109631476","https://openalex.org/W3109791956","https://openalex.org/W3114224083","https://openalex.org/W3130800560","https://openalex.org/W3144867668","https://openalex.org/W3156476459","https://openalex.org/W3157716083","https://openalex.org/W3176912151","https://openalex.org/W3177433851","https://openalex.org/W3205531468","https://openalex.org/W4205444807","https://openalex.org/W4210422063","https://openalex.org/W4223611254","https://openalex.org/W4283313139","https://openalex.org/W4285102269","https://openalex.org/W4285240001","https://openalex.org/W4286254499","https://openalex.org/W4286580809","https://openalex.org/W4298857966","https://openalex.org/W4302512962","https://openalex.org/W6637967152","https://openalex.org/W6684205842","https://openalex.org/W6684921986","https://openalex.org/W6696273291","https://openalex.org/W6718092244","https://openalex.org/W6745347688","https://openalex.org/W6746163721","https://openalex.org/W6760782946","https://openalex.org/W6792522911","https://openalex.org/W6793108136"],"related_works":["https://openalex.org/W2502115930","https://openalex.org/W2482350142","https://openalex.org/W4246396837","https://openalex.org/W3126451824","https://openalex.org/W1561927205","https://openalex.org/W3191453585","https://openalex.org/W4297672492","https://openalex.org/W4310988119","https://openalex.org/W2331917905","https://openalex.org/W3155039083"],"abstract_inverted_index":{"Although":[0],"the":[1,8,22,29,61,66,71,77,80,84,91,102,107,114,125,132,142,153,161,164,169,175,180,192,211,214,219,230,239,256,263,267],"issue":[2],"of":[3,11,24,32,70,79,93,111,118,127,135,145,258,266],"sparse":[4,128],"expert":[5,109,115,129,166,221],"samples":[6,95,105,110,130,167,172,206,217,260],"at":[7,131,229],"early":[9,133],"stage":[10,134],"training":[12,269],"in":[13,35,87,238,248],"inverse":[14,47],"reinforcement":[15,48],"learning":[16,49],"(IRL)":[17],"is":[18,51,188],"successfully":[19],"resolved":[20],"by":[21,174,270],"introduction":[23],"generative":[25,45],"adversarial":[26,46,97],"network":[27,268],"(GAN),":[28],"inherent":[30],"drawbacks":[31],"GAN":[33,73,81,149],"result":[34],"ineffective":[36],"generated":[37,173],"samples.":[38],"Therefore,":[39],"we":[40,100,158,224],"propose":[41],"an":[42],"algorithm":[43],"for":[44,196,273,281],"that":[50,252],"based":[52,82],"on":[53,83,201],"deep":[54],"deterministic":[55,62],"policy":[56,197],"gradient":[57],"(DDPG).":[58],"We":[59],"use":[60],"strategy":[63,177],"to":[64,89,178,190,226,278],"replace":[65],"random":[67],"noise":[68],"input":[69],"initial":[72,176],"model":[74,254],"and":[75,168,199,218,233,244,261],"reconstruct":[76],"generator":[78],"Actor-Critic":[85],"mechanism":[86],"order":[88],"improve":[90],"quality":[92,257],"GAN-generated":[94,103,259],"during":[96],"training.":[98],"Meanwhile,":[99],"mix":[101],"virtual":[104],"with":[106],"original":[108],"IRL":[112,146,155],"as":[113],"sample":[116,222],"set":[117],"IRL.":[119],"Our":[120],"approach":[121],"not":[122],"only":[123],"solves":[124],"problem":[126],"training,":[136],"but":[137],"most":[138],"importantly,":[139],"it":[140],"makes":[141],"decision-making":[143,156],"process":[144,194],"occurring":[147],"under":[148],"more":[150],"efficient.":[151],"In":[152],"subsequent":[154],"process,":[157],"also":[159],"analyze":[160],"differences":[162,212],"between":[163,213],"mixed":[165,220],"non-expert":[170,204,216],"trajectory":[171,205,245],"determine":[179],"best":[181],"reward":[182,186,231],"function.":[183],"The":[184],"learned":[185],"function":[187,232],"used":[189],"drive":[191],"RL":[193],"positively":[195],"updating":[198],"optimization,":[200],"which":[202],"further":[203],"are":[207],"generated.":[208],"By":[209],"comparing":[210],"new":[215],"set,":[223],"hope":[225],"iteratively":[227],"arrive":[228],"optimal":[234],"policy.":[235],"Performance":[236],"tests":[237],"MuJoCo":[240],"physical":[241],"simulation":[242],"environment":[243],"prediction":[246],"experiments":[247],"Grid":[249],"World":[250],"show":[251],"our":[253],"improves":[255],"reduces":[262],"computational":[264],"cost":[265],"approximately":[271],"20%":[272],"each":[274],"given":[275],"environment,":[276],"applying":[277],"decision":[279],"planning":[280],"autonomous":[282],"driving.":[283]},"counts_by_year":[{"year":2025,"cited_by_count":2},{"year":2023,"cited_by_count":2}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}
