{"id":"https://openalex.org/W7153056031","doi":"https://doi.org/10.48550/arxiv.2604.07784","title":"Automotive Engineering-Centric Agentic AI Workflow Framework","display_name":"Automotive Engineering-Centric Agentic AI Workflow Framework","publication_year":2026,"publication_date":"2026-04-09","ids":{"openalex":"https://openalex.org/W7153056031","doi":"https://doi.org/10.48550/arxiv.2604.07784"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2604.07784","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.07784","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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","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.2604.07784","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5031968749","display_name":"Tong Duy Son","orcid":"https://orcid.org/0000-0002-4680-3779"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Son, Tong Duy","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100421209","display_name":"Zhihao Liu","orcid":"https://orcid.org/0000-0002-0222-912X"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Liu, Zhihao","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5086934575","display_name":"Piero Brigida","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Brigida, Piero","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5067082512","display_name":"Yerlan Akhmetov","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Akhmetov, Yerlan","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5010181996","display_name":"G. V. Devarajan","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Devarajan, Gurudevan","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5133362163","display_name":"Kai Liu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Liu, Kai","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5053763482","display_name":"Ajinkya Bhave","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Bhave, Ajinkya","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/T10906","display_name":"AI-based Problem Solving and Planning","score":0.22020000219345093,"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/T10906","display_name":"AI-based Problem Solving and Planning","score":0.22020000219345093,"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/T12000","display_name":"Systems Engineering Methodologies and Applications","score":0.062199998646974564,"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/T10848","display_name":"Advanced Multi-Objective Optimization Algorithms","score":0.05950000137090683,"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/workflow","display_name":"Workflow","score":0.7846999764442444},{"id":"https://openalex.org/keywords/automotive-industry","display_name":"Automotive industry","score":0.4724000096321106},{"id":"https://openalex.org/keywords/feature-engineering","display_name":"Feature engineering","score":0.4699000120162964},{"id":"https://openalex.org/keywords/reinforcement-learning","display_name":"Reinforcement learning","score":0.3447999954223633},{"id":"https://openalex.org/keywords/knowledge-engineering","display_name":"Knowledge engineering","score":0.33739998936653137},{"id":"https://openalex.org/keywords/engineering-design-process","display_name":"Engineering design process","score":0.33160001039505005},{"id":"https://openalex.org/keywords/automation","display_name":"Automation","score":0.3262999951839447}],"concepts":[{"id":"https://openalex.org/C177212765","wikidata":"https://www.wikidata.org/wiki/Q627335","display_name":"Workflow","level":2,"score":0.7846999764442444},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5479000210762024},{"id":"https://openalex.org/C526921623","wikidata":"https://www.wikidata.org/wiki/Q190117","display_name":"Automotive industry","level":2,"score":0.4724000096321106},{"id":"https://openalex.org/C2778827112","wikidata":"https://www.wikidata.org/wiki/Q22245680","display_name":"Feature engineering","level":3,"score":0.4699000120162964},{"id":"https://openalex.org/C115903868","wikidata":"https://www.wikidata.org/wiki/Q80993","display_name":"Software engineering","level":1,"score":0.42179998755455017},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4052000045776367},{"id":"https://openalex.org/C201995342","wikidata":"https://www.wikidata.org/wiki/Q682496","display_name":"Systems engineering","level":1,"score":0.37940001487731934},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.36149999499320984},{"id":"https://openalex.org/C97541855","wikidata":"https://www.wikidata.org/wiki/Q830687","display_name":"Reinforcement learning","level":2,"score":0.3447999954223633},{"id":"https://openalex.org/C84685590","wikidata":"https://www.wikidata.org/wiki/Q1540472","display_name":"Knowledge engineering","level":2,"score":0.33739998936653137},{"id":"https://openalex.org/C34972735","wikidata":"https://www.wikidata.org/wiki/Q2920267","display_name":"Engineering design process","level":2,"score":0.33160001039505005},{"id":"https://openalex.org/C115901376","wikidata":"https://www.wikidata.org/wiki/Q184199","display_name":"Automation","level":2,"score":0.3262999951839447},{"id":"https://openalex.org/C157170001","wikidata":"https://www.wikidata.org/wiki/Q4781507","display_name":"Applications of artificial intelligence","level":2,"score":0.2921999990940094},{"id":"https://openalex.org/C95764724","wikidata":"https://www.wikidata.org/wiki/Q7663738","display_name":"System of systems engineering","level":3,"score":0.27239999175071716},{"id":"https://openalex.org/C34413123","wikidata":"https://www.wikidata.org/wiki/Q170978","display_name":"Robotics","level":3,"score":0.25920000672340393},{"id":"https://openalex.org/C44280652","wikidata":"https://www.wikidata.org/wiki/Q104837","display_name":"Phase (matter)","level":2,"score":0.25859999656677246},{"id":"https://openalex.org/C2775924081","wikidata":"https://www.wikidata.org/wiki/Q55608371","display_name":"Control (management)","level":2,"score":0.2574000060558319},{"id":"https://openalex.org/C527412718","wikidata":"https://www.wikidata.org/wiki/Q855395","display_name":"Interpretation (philosophy)","level":2,"score":0.2563000023365021}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2604.07784","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.07784","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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"Preprint"}],"best_oa_location":{"id":"doi:10.48550/arxiv.2604.07784","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.07784","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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Preprint"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Engineering":[0,46],"workflows":[1,56,143],"such":[2],"as":[3,31,36,57,107,112,157],"design":[4],"optimization,":[5],"simulation-based":[6],"diagnosis,":[7],"control":[8],"tuning,":[9,131],"and":[10,18,82,93,115,138,163],"model-based":[11],"systems":[12],"engineering":[13,55,71,79,104,133,155],"(MBSE)":[14],"are":[15],"iterative,":[16],"constraint-driven,":[17],"shaped":[19],"by":[20],"prior":[21],"decisions.":[22],"Yet":[23],"many":[24],"AI":[25,65,156],"methods":[26],"still":[27],"treat":[28],"these":[29],"activities":[30],"isolated":[32],"tasks":[33],"rather":[34],"than":[35],"parts":[37],"of":[38,160],"a":[39,148,158,165],"broader":[40],"workflow.":[41],"This":[42],"paper":[43,153],"presents":[44],"Agentic":[45],"Intelligence":[47],"(AEI),":[48],"an":[49,75,86],"industrial":[50,173],"vision":[51],"framework":[52],"that":[53],"models":[54],"constrained,":[58],"history-aware":[59],"sequential":[60],"decision":[61,94],"processes":[62],"in":[63,102,126,172],"which":[64,103],"agents":[66,110],"support":[67],"engineer-supervised":[68],"interventions":[69],"over":[70],"toolchains.":[72],"AEI":[73],"links":[74],"offline":[76],"phase":[77,88],"for":[78,89,119,168],"data":[80],"processing":[81],"workflow-memory":[83],"construction":[84],"with":[85],"online":[87],"workflow-state":[90],"estimation,":[91],"retrieval,":[92],"support.":[95],"A":[96],"control-theoretic":[97],"interpretation":[98],"is":[99],"also":[100],"possible,":[101],"objectives":[105],"act":[106,111],"reference":[108],"signals,":[109],"workflow":[113],"controllers,":[114],"toolchains":[116],"provide":[117],"feedback":[118],"intervention":[120],"selection.":[121],"Representative":[122],"automotive":[123],"use":[124],"cases":[125],"suspension":[127],"design,":[128],"reinforcement":[129],"learning":[130],"multimodal":[132],"knowledge":[134],"reuse,":[135],"aerodynamic":[136],"exploration,":[137],"MBSE":[139],"show":[140],"how":[141],"diverse":[142],"can":[144],"be":[145],"expressed":[146],"within":[147],"common":[149],"formulation.":[150],"Overall,":[151],"the":[152],"positions":[154],"problem":[159],"process-level":[161],"intelligence":[162],"outlines":[164],"practical":[166],"roadmap":[167],"future":[169],"empirical":[170],"validation":[171],"settings.":[174]},"counts_by_year":[],"updated_date":"2026-07-28T07:46:37.118299","created_date":"2026-04-11T00:00:00"}