{"id":"https://openalex.org/W7158986739","doi":"https://doi.org/10.48550/arxiv.2604.26126","title":"Application of Deep Reinforcement Learning to Event-Triggered Control for Networked Artificial Pancreas Systems","display_name":"Application of Deep Reinforcement Learning to Event-Triggered Control for Networked Artificial Pancreas Systems","publication_year":2026,"publication_date":"2026-04-28","ids":{"openalex":"https://openalex.org/W7158986739","doi":"https://doi.org/10.48550/arxiv.2604.26126"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2604.26126","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.26126","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Preprint"},"type":"preprint","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.48550/arxiv.2604.26126","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5070836427","display_name":"Junya Ikemoto","orcid":"https://orcid.org/0000-0002-0145-3381"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Ikemoto, Junya","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5134900034","display_name":"Satoshi Maruyama","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Maruyama, Satoshi","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5025704398","display_name":"Kazumune Hashimoto","orcid":"https://orcid.org/0000-0002-9376-5760"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Hashimoto, Kazumune","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10046","display_name":"Stability and Control of Uncertain Systems","score":0.09480000287294388,"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"}},"topics":[{"id":"https://openalex.org/T10046","display_name":"Stability and Control of Uncertain Systems","score":0.09480000287294388,"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/T10675","display_name":"Mechanical Circulatory Support Devices","score":0.08879999816417694,"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"}},{"id":"https://openalex.org/T10791","display_name":"Advanced Control Systems Optimization","score":0.08659999817609787,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/reinforcement-learning","display_name":"Reinforcement learning","score":0.7785000205039978},{"id":"https://openalex.org/keywords/controller","display_name":"Controller (irrigation)","score":0.5386000275611877},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.5297999978065491},{"id":"https://openalex.org/keywords/reduction","display_name":"Reduction (mathematics)","score":0.49880000948905945},{"id":"https://openalex.org/keywords/artificial-pancreas","display_name":"Artificial pancreas","score":0.4832000136375427},{"id":"https://openalex.org/keywords/control","display_name":"Control (management)","score":0.4797999858856201},{"id":"https://openalex.org/keywords/control-system","display_name":"Control system","score":0.43869999051094055},{"id":"https://openalex.org/keywords/networked-control-system","display_name":"Networked control system","score":0.41589999198913574}],"concepts":[{"id":"https://openalex.org/C97541855","wikidata":"https://www.wikidata.org/wiki/Q830687","display_name":"Reinforcement learning","level":2,"score":0.7785000205039978},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6406000256538391},{"id":"https://openalex.org/C203479927","wikidata":"https://www.wikidata.org/wiki/Q5165939","display_name":"Controller (irrigation)","level":2,"score":0.5386000275611877},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.5297999978065491},{"id":"https://openalex.org/C111335779","wikidata":"https://www.wikidata.org/wiki/Q3454686","display_name":"Reduction (mathematics)","level":2,"score":0.49880000948905945},{"id":"https://openalex.org/C2780353609","wikidata":"https://www.wikidata.org/wiki/Q1569064","display_name":"Artificial pancreas","level":4,"score":0.4832000136375427},{"id":"https://openalex.org/C2775924081","wikidata":"https://www.wikidata.org/wiki/Q55608371","display_name":"Control (management)","level":2,"score":0.4797999858856201},{"id":"https://openalex.org/C133731056","wikidata":"https://www.wikidata.org/wiki/Q4917288","display_name":"Control engineering","level":1,"score":0.44690001010894775},{"id":"https://openalex.org/C17500928","wikidata":"https://www.wikidata.org/wiki/Q959968","display_name":"Control system","level":2,"score":0.43869999051094055},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.41940000653266907},{"id":"https://openalex.org/C1759631","wikidata":"https://www.wikidata.org/wiki/Q9336345","display_name":"Networked control system","level":3,"score":0.41589999198913574},{"id":"https://openalex.org/C47446073","wikidata":"https://www.wikidata.org/wiki/Q5165890","display_name":"Control theory (sociology)","level":3,"score":0.37540000677108765},{"id":"https://openalex.org/C91575142","wikidata":"https://www.wikidata.org/wiki/Q1971426","display_name":"Optimal control","level":2,"score":0.33980000019073486},{"id":"https://openalex.org/C155386361","wikidata":"https://www.wikidata.org/wiki/Q1649571","display_name":"Process control","level":3,"score":0.3377000093460083},{"id":"https://openalex.org/C126042441","wikidata":"https://www.wikidata.org/wiki/Q1324888","display_name":"Frame (networking)","level":2,"score":0.31040000915527344},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.2879999876022339},{"id":"https://openalex.org/C77618280","wikidata":"https://www.wikidata.org/wiki/Q1155772","display_name":"Scheme (mathematics)","level":2,"score":0.2727000117301941},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.26269999146461487},{"id":"https://openalex.org/C188116033","wikidata":"https://www.wikidata.org/wiki/Q2664563","display_name":"Q-learning","level":3,"score":0.2558000087738037}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2604.26126","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.26126","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"Preprint"}],"best_oa_location":{"id":"doi:10.48550/arxiv.2604.26126","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.26126","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Preprint"},"sustainable_development_goals":[{"score":0.7275583148002625,"display_name":"Affordable and clean energy","id":"https://metadata.un.org/sdg/7"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"This":[0],"paper":[1],"proposes":[2],"a":[3,32,71,84,94,108,117],"deep":[4],"reinforcement":[5],"learning":[6,50,63,79],"(DRL)-based":[7],"event-triggered":[8],"controller":[9,74],"design":[10,75],"for":[11,113],"networked":[12,27],"artificial":[13],"pancreas":[14],"(AP)":[15],"systems.":[16],"Although":[17],"existing":[18],"DRL-based":[19,73],"AP":[20],"controllers":[21],"typically":[22],"assume":[23],"periodic":[24],"control":[25,28,46,133],"updates,":[26],"systems":[29],"(NCSs)":[30],"require":[31],"reduction":[33],"in":[34,90],"communication":[35,129],"frequency":[36],"to":[37,45],"achieve":[38],"energy-efficient":[39],"operation,":[40],"which":[41,114],"is":[42,104],"directly":[43],"tied":[44],"updates.":[47],"However,":[48],"jointly":[49],"both":[51],"insulin":[52],"dosing":[53],"and":[54,101],"update":[55,80],"timing":[56,81],"significantly":[57],"increases":[58],"the":[59,62,102,125],"complexity":[60],"of":[61],"problem.":[64],"To":[65],"alleviate":[66],"this":[67],"complexity,":[68],"we":[69,115],"develop":[70],"practical":[72],"that":[76,124],"avoids":[77],"explicitly":[78],"by":[82,88],"introducing":[83],"rule-based":[85],"criterion":[86],"defined":[87],"changes":[89],"blood":[91],"glucose.":[92],"As":[93],"result,":[95],"decision-making":[96],"occurs":[97],"at":[98],"irregular":[99],"intervals,":[100],"problem":[103],"naturally":[105],"formulated":[106],"as":[107],"semi-Markov":[109],"decision":[110],"process":[111],"(SMDP),":[112],"extend":[116],"standard":[118],"DRL":[119],"algorithm.":[120],"Numerical":[121],"experiments":[122],"demonstrate":[123],"proposed":[126],"method":[127],"improves":[128],"efficiency":[130],"while":[131],"maintaining":[132],"performance.":[134]},"counts_by_year":[],"updated_date":"2026-07-28T07:46:37.118299","created_date":"2026-05-01T00:00:00"}
