{"id":"https://openalex.org/W4321483873","doi":"https://doi.org/10.1109/tnnls.2023.3244024","title":"Improvement of Reinforcement Learning With Supermodularity","display_name":"Improvement of Reinforcement Learning With Supermodularity","publication_year":2023,"publication_date":"2023-02-22","ids":{"openalex":"https://openalex.org/W4321483873","doi":"https://doi.org/10.1109/tnnls.2023.3244024","pmid":"https://pubmed.ncbi.nlm.nih.gov/37027690"},"language":"en","primary_location":{"id":"doi:10.1109/tnnls.2023.3244024","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tnnls.2023.3244024","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/A5101795886","display_name":"Ying Meng","orcid":"https://orcid.org/0000-0002-9504-3745"},"institutions":[{"id":"https://openalex.org/I9224756","display_name":"Northeastern University","ror":"https://ror.org/03awzbc87","country_code":"CN","type":"education","lineage":["https://openalex.org/I9224756"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ying Meng","raw_affiliation_strings":["National Frontiers Science Center for Industrial Intelligence and Systems Optimization and the Key Laboratory of Data Analytics and Optimization for Smart Industry, Ministry of Education, Northeastern University, Shenyang, China"],"raw_orcid":"https://orcid.org/0000-0002-9504-3745","affiliations":[{"raw_affiliation_string":"National Frontiers Science Center for Industrial Intelligence and Systems Optimization and the Key Laboratory of Data Analytics and Optimization for Smart Industry, Ministry of Education, Northeastern University, Shenyang, China","institution_ids":["https://openalex.org/I9224756"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5048009528","display_name":"Fengyuan Shi","orcid":"https://orcid.org/0000-0002-1689-5473"},"institutions":[{"id":"https://openalex.org/I9224756","display_name":"Northeastern University","ror":"https://ror.org/03awzbc87","country_code":"CN","type":"education","lineage":["https://openalex.org/I9224756"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Fengyuan Shi","raw_affiliation_strings":["Key Laboratory of Data Analytics and Optimization for Smart Industry, Ministry of Education, Liaoning Engineering Laboratory of Data Analytics and Optimization for Smart Industry, Northeastern University, Shenyang, China"],"raw_orcid":"https://orcid.org/0000-0002-1689-5473","affiliations":[{"raw_affiliation_string":"Key Laboratory of Data Analytics and Optimization for Smart Industry, Ministry of Education, Liaoning Engineering Laboratory of Data Analytics and Optimization for Smart Industry, Northeastern University, Shenyang, China","institution_ids":["https://openalex.org/I9224756"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5080304378","display_name":"Lixin Tang","orcid":"https://orcid.org/0000-0002-9950-5169"},"institutions":[{"id":"https://openalex.org/I9224756","display_name":"Northeastern University","ror":"https://ror.org/03awzbc87","country_code":"CN","type":"education","lineage":["https://openalex.org/I9224756"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Lixin Tang","raw_affiliation_strings":["National Frontiers Science Center for Industrial Intelligence and Systems Optimization, Northeastern University, Shenyang, China"],"raw_orcid":"https://orcid.org/0000-0002-9950-5169","affiliations":[{"raw_affiliation_string":"National Frontiers Science Center for Industrial Intelligence and Systems Optimization, Northeastern University, Shenyang, China","institution_ids":["https://openalex.org/I9224756"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5101886365","display_name":"Defeng Sun","orcid":"https://orcid.org/0000-0002-6699-6272"},"institutions":[{"id":"https://openalex.org/I9224756","display_name":"Northeastern University","ror":"https://ror.org/03awzbc87","country_code":"CN","type":"education","lineage":["https://openalex.org/I9224756"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Defeng Sun","raw_affiliation_strings":["National Frontiers Science Center for Industrial Intelligence and Systems Optimization and the Key Laboratory of Data Analytics and Optimization for Smart Industry, Ministry of Education, Northeastern University, Shenyang, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"National Frontiers Science Center for Industrial Intelligence and Systems Optimization and the Key Laboratory of Data Analytics and Optimization for Smart Industry, Ministry of Education, Northeastern University, Shenyang, China","institution_ids":["https://openalex.org/I9224756"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I9224756"],"apc_list":null,"apc_paid":null,"fwci":0.6345,"has_fulltext":false,"cited_by_count":4,"citation_normalized_percentile":{"value":0.71536799,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":98},"biblio":{"volume":"34","issue":"9","first_page":"5298","last_page":"5309"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10462","display_name":"Reinforcement Learning in Robotics","score":0.9991000294685364,"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":0.9991000294685364,"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":0.9927999973297119,"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"}},{"id":"https://openalex.org/T10848","display_name":"Advanced Multi-Objective Optimization Algorithms","score":0.9778000116348267,"subfield":{"id":"https://openalex.org/subfields/1703","display_name":"Computational Theory and Mathematics"},"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":0.8279078006744385},{"id":"https://openalex.org/keywords/markov-decision-process","display_name":"Markov decision process","score":0.7599759697914124},{"id":"https://openalex.org/keywords/monotonic-function","display_name":"Monotonic function","score":0.7319347858428955},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6535694599151611},{"id":"https://openalex.org/keywords/mathematical-optimization","display_name":"Mathematical optimization","score":0.6309701204299927},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.6159418821334839},{"id":"https://openalex.org/keywords/parameterized-complexity","display_name":"Parameterized complexity","score":0.5848881602287292},{"id":"https://openalex.org/keywords/state-space","display_name":"State space","score":0.5668558478355408},{"id":"https://openalex.org/keywords/action","display_name":"Action (physics)","score":0.486736536026001},{"id":"https://openalex.org/keywords/decision-problem","display_name":"Decision problem","score":0.46740487217903137},{"id":"https://openalex.org/keywords/monotone-polygon","display_name":"Monotone polygon","score":0.4500652551651001},{"id":"https://openalex.org/keywords/state","display_name":"State (computer science)","score":0.412163645029068},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.3287312388420105},{"id":"https://openalex.org/keywords/markov-process","display_name":"Markov process","score":0.3156912922859192},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.29719778895378113},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.20981478691101074}],"concepts":[{"id":"https://openalex.org/C97541855","wikidata":"https://www.wikidata.org/wiki/Q830687","display_name":"Reinforcement learning","level":2,"score":0.8279078006744385},{"id":"https://openalex.org/C106189395","wikidata":"https://www.wikidata.org/wiki/Q176789","display_name":"Markov decision process","level":3,"score":0.7599759697914124},{"id":"https://openalex.org/C72169020","wikidata":"https://www.wikidata.org/wiki/Q194404","display_name":"Monotonic function","level":2,"score":0.7319347858428955},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6535694599151611},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.6309701204299927},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.6159418821334839},{"id":"https://openalex.org/C165464430","wikidata":"https://www.wikidata.org/wiki/Q1570441","display_name":"Parameterized complexity","level":2,"score":0.5848881602287292},{"id":"https://openalex.org/C72434380","wikidata":"https://www.wikidata.org/wiki/Q230930","display_name":"State space","level":2,"score":0.5668558478355408},{"id":"https://openalex.org/C2780791683","wikidata":"https://www.wikidata.org/wiki/Q846785","display_name":"Action (physics)","level":2,"score":0.486736536026001},{"id":"https://openalex.org/C115988155","wikidata":"https://www.wikidata.org/wiki/Q3262192","display_name":"Decision problem","level":2,"score":0.46740487217903137},{"id":"https://openalex.org/C2834757","wikidata":"https://www.wikidata.org/wiki/Q4925424","display_name":"Monotone polygon","level":2,"score":0.4500652551651001},{"id":"https://openalex.org/C48103436","wikidata":"https://www.wikidata.org/wiki/Q599031","display_name":"State (computer science)","level":2,"score":0.412163645029068},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.3287312388420105},{"id":"https://openalex.org/C159886148","wikidata":"https://www.wikidata.org/wiki/Q176645","display_name":"Markov process","level":2,"score":0.3156912922859192},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.29719778895378113},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.20981478691101074},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.0},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.0},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C13280743","wikidata":"https://www.wikidata.org/wiki/Q131089","display_name":"Geodesy","level":1,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/tnnls.2023.3244024","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tnnls.2023.3244024","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:37027690","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/37027690","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":[{"display_name":"Peace, Justice and strong institutions","score":0.800000011920929,"id":"https://metadata.un.org/sdg/16"}],"awards":[{"id":"https://openalex.org/G2311391187","display_name":null,"funder_award_id":"B16009","funder_id":"https://openalex.org/F4320327912","funder_display_name":"Higher Education Discipline Innovation Project"},{"id":"https://openalex.org/G3596273737","display_name":"\u5e26\u6709\u67d4\u6027\u9700\u6c42\u7279\u5f81\u7684\u4e24\u9636\u6bb5\u576f\u6599\u8ba1\u5212\u4e0e\u8c03\u5ea6\u95ee\u9898\u7814\u7a76","funder_award_id":"72002028","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G5303336969","display_name":null,"funder_award_id":"72192830","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G852931893","display_name":null,"funder_award_id":"72192831","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"},{"id":"https://openalex.org/F4320327912","display_name":"Higher Education Discipline Innovation Project","ror":null}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":50,"referenced_works":["https://openalex.org/W389907844","https://openalex.org/W1626155273","https://openalex.org/W1757796397","https://openalex.org/W1984214681","https://openalex.org/W2013067314","https://openalex.org/W2045665199","https://openalex.org/W2058653357","https://openalex.org/W2091565802","https://openalex.org/W2145339207","https://openalex.org/W2152028815","https://openalex.org/W2155027007","https://openalex.org/W2155312717","https://openalex.org/W2201581102","https://openalex.org/W2342137734","https://openalex.org/W2736601468","https://openalex.org/W2766447205","https://openalex.org/W2886869472","https://openalex.org/W2888329226","https://openalex.org/W2913726715","https://openalex.org/W2923512171","https://openalex.org/W2948268323","https://openalex.org/W2951799221","https://openalex.org/W2963864421","https://openalex.org/W2964043796","https://openalex.org/W2966162984","https://openalex.org/W2966349401","https://openalex.org/W2977955221","https://openalex.org/W3080409317","https://openalex.org/W3080626793","https://openalex.org/W3121269786","https://openalex.org/W3168202624","https://openalex.org/W3169375224","https://openalex.org/W3173319990","https://openalex.org/W3175494061","https://openalex.org/W4214660441","https://openalex.org/W4214717370","https://openalex.org/W4226257065","https://openalex.org/W4295138992","https://openalex.org/W4298857966","https://openalex.org/W4315473650","https://openalex.org/W6683204974","https://openalex.org/W6684921986","https://openalex.org/W6685444567","https://openalex.org/W6687681856","https://openalex.org/W6692846177","https://openalex.org/W6725207838","https://openalex.org/W6741002519","https://openalex.org/W6748487558","https://openalex.org/W6758697878","https://openalex.org/W6763777643"],"related_works":["https://openalex.org/W2049472152","https://openalex.org/W2807018115","https://openalex.org/W4388236136","https://openalex.org/W4200250224","https://openalex.org/W2606546905","https://openalex.org/W2126560268","https://openalex.org/W2606518309","https://openalex.org/W2285658092","https://openalex.org/W2482498454","https://openalex.org/W2947128950"],"abstract_inverted_index":{"Reinforcement":[0],"learning":[1,9],"(RL)":[2],"is":[3],"a":[4,14,55,88,124],"promising":[5],"approach":[6],"to":[7,37,81,109,127],"tackling":[8],"and":[10,103,148,168],"decision-making":[11],"problems":[12,79],"in":[13,49,85,152,165],"dynamic":[15],"environment.":[16],"Most":[17],"studies":[18],"on":[19,22,160],"RL":[20,172],"focus":[21],"the":[23,46,50,68,82,96,99,104,117,132,146,157,161,166,170,182,188],"improvement":[24],"of":[25,57,75,98,190],"state":[26,62,110],"evaluation":[27],"or":[28,70],"action":[29,39,101,133],"evaluation.":[30],"In":[31],"this":[32],"article,":[33],"we":[34,122,143,155],"investigate":[35],"how":[36,145],"reduce":[38],"space":[40],"by":[41,115],"using":[42,116],"supermodularity.":[43],"We":[44],"consider":[45],"decision":[47,52,91],"tasks":[48],"multistage":[51],"process":[53,92],"as":[54,140],"collection":[56],"parameterized":[58,77],"optimization":[59,78],"problems,":[60],"where":[61],"parameters":[63,111],"dynamically":[64],"vary":[65],"along":[66],"with":[67,94,107,173],"time":[69],"stage.":[71],"The":[72,178],"optimal":[73,83,100,105],"solutions":[74],"these":[76],"correspond":[80],"actions":[84,130],"RL.":[86,153,191],"For":[87],"given":[89],"Markov":[90],"(MDP)":[93],"supermodularity,":[95],"monotonicity":[97,125,149,158,183],"set":[102],"selection":[106],"respect":[108],"can":[112,185],"be":[113],"obtained":[114],"monotone":[118],"comparative":[119],"statics.":[120],"Accordingly,":[121],"propose":[123],"cut":[126,150,159,184],"remove":[128],"unpromising":[129],"from":[131],"space.":[134],"Taking":[135],"bin":[136],"packing":[137],"problem":[138],"(BPP)":[139],"an":[141],"example,":[142],"show":[144,180],"supermodularity":[147],"work":[151],"Finally,":[154],"evaluate":[156],"benchmark":[162],"datasets":[163],"reported":[164],"literature":[167],"compare":[169],"proposed":[171],"some":[174],"popular":[175],"baseline":[176],"algorithms.":[177],"results":[179],"that":[181],"effectively":[186],"improve":[187],"performance":[189]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":1},{"year":2023,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}