{"id":"https://openalex.org/W4206971884","doi":"https://doi.org/10.1109/ssci50451.2021.9659552","title":"Interpretable AI Agent Through Nonlinear Decision Trees for Lane Change Problem","display_name":"Interpretable AI Agent Through Nonlinear Decision Trees for Lane Change Problem","publication_year":2021,"publication_date":"2021-12-05","ids":{"openalex":"https://openalex.org/W4206971884","doi":"https://doi.org/10.1109/ssci50451.2021.9659552"},"language":"en","primary_location":{"id":"doi:10.1109/ssci50451.2021.9659552","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ssci50451.2021.9659552","pdf_url":null,"source":{"id":"https://openalex.org/S4363604921","display_name":"2021 IEEE Symposium Series on Computational Intelligence (SSCI)","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":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 IEEE Symposium Series on Computational Intelligence (SSCI)","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"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/A5006499382","display_name":"Abhiroop Ghosh","orcid":"https://orcid.org/0000-0003-3251-5941"},"institutions":[{"id":"https://openalex.org/I87216513","display_name":"Michigan State University","ror":"https://ror.org/05hs6h993","country_code":"US","type":"education","lineage":["https://openalex.org/I87216513"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Abhiroop Ghosh","raw_affiliation_strings":["Michigan State University,East Lansing,USA","Michigan State University, East Lansing, USA"],"affiliations":[{"raw_affiliation_string":"Michigan State University,East Lansing,USA","institution_ids":["https://openalex.org/I87216513"]},{"raw_affiliation_string":"Michigan State University, East Lansing, USA","institution_ids":["https://openalex.org/I87216513"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5068379698","display_name":"Yashesh Dhebar","orcid":"https://orcid.org/0000-0001-8144-0566"},"institutions":[{"id":"https://openalex.org/I87216513","display_name":"Michigan State University","ror":"https://ror.org/05hs6h993","country_code":"US","type":"education","lineage":["https://openalex.org/I87216513"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Yashesh Dhebar","raw_affiliation_strings":["Michigan State University,East Lansing,USA","Michigan State University, East Lansing, USA"],"affiliations":[{"raw_affiliation_string":"Michigan State University,East Lansing,USA","institution_ids":["https://openalex.org/I87216513"]},{"raw_affiliation_string":"Michigan State University, East Lansing, USA","institution_ids":["https://openalex.org/I87216513"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5049905796","display_name":"Ritam Guha","orcid":"https://orcid.org/0000-0002-1375-777X"},"institutions":[{"id":"https://openalex.org/I87216513","display_name":"Michigan State University","ror":"https://ror.org/05hs6h993","country_code":"US","type":"education","lineage":["https://openalex.org/I87216513"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Ritam Guha","raw_affiliation_strings":["Michigan State University,East Lansing,USA","Michigan State University, East Lansing, USA"],"affiliations":[{"raw_affiliation_string":"Michigan State University,East Lansing,USA","institution_ids":["https://openalex.org/I87216513"]},{"raw_affiliation_string":"Michigan State University, East Lansing, USA","institution_ids":["https://openalex.org/I87216513"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5088394271","display_name":"Kalyanmoy Deb","orcid":"https://orcid.org/0000-0001-7402-9939"},"institutions":[{"id":"https://openalex.org/I87216513","display_name":"Michigan State University","ror":"https://ror.org/05hs6h993","country_code":"US","type":"education","lineage":["https://openalex.org/I87216513"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Kalyanmoy Deb","raw_affiliation_strings":["Michigan State University,East Lansing,USA","Michigan State University, East Lansing, USA"],"affiliations":[{"raw_affiliation_string":"Michigan State University,East Lansing,USA","institution_ids":["https://openalex.org/I87216513"]},{"raw_affiliation_string":"Michigan State University, East Lansing, USA","institution_ids":["https://openalex.org/I87216513"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5061604841","display_name":"Subramanya Nageshrao","orcid":null},"institutions":[{"id":"https://openalex.org/I1292974536","display_name":"Ford Motor Company (United States)","ror":"https://ror.org/00g2tkw06","country_code":"US","type":"company","lineage":["https://openalex.org/I1292974536"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Subramanya Nageshrao","raw_affiliation_strings":["Ford Motor Company,Dearborn,USA","Ford Motor Company, Dearborn, USA"],"affiliations":[{"raw_affiliation_string":"Ford Motor Company,Dearborn,USA","institution_ids":["https://openalex.org/I1292974536"]},{"raw_affiliation_string":"Ford Motor Company, Dearborn, USA","institution_ids":["https://openalex.org/I1292974536"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5088648447","display_name":"Ling Zhu","orcid":"https://orcid.org/0000-0003-3887-7863"},"institutions":[{"id":"https://openalex.org/I1292974536","display_name":"Ford Motor Company (United States)","ror":"https://ror.org/00g2tkw06","country_code":"US","type":"company","lineage":["https://openalex.org/I1292974536"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Ling Zhu","raw_affiliation_strings":["Ford Motor Company,Dearborn,USA","Ford Motor Company, Dearborn, USA"],"affiliations":[{"raw_affiliation_string":"Ford Motor Company,Dearborn,USA","institution_ids":["https://openalex.org/I1292974536"]},{"raw_affiliation_string":"Ford Motor Company, Dearborn, USA","institution_ids":["https://openalex.org/I1292974536"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5020219990","display_name":"Eric Tseng","orcid":null},"institutions":[{"id":"https://openalex.org/I1292974536","display_name":"Ford Motor Company (United States)","ror":"https://ror.org/00g2tkw06","country_code":"US","type":"company","lineage":["https://openalex.org/I1292974536"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Eric Tseng","raw_affiliation_strings":["Ford Motor Company,Dearborn,USA","Ford Motor Company, Dearborn, USA"],"affiliations":[{"raw_affiliation_string":"Ford Motor Company,Dearborn,USA","institution_ids":["https://openalex.org/I1292974536"]},{"raw_affiliation_string":"Ford Motor Company, Dearborn, USA","institution_ids":["https://openalex.org/I1292974536"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5015550681","display_name":"Dimitar Filev","orcid":"https://orcid.org/0000-0001-7127-6782"},"institutions":[{"id":"https://openalex.org/I1292974536","display_name":"Ford Motor Company (United States)","ror":"https://ror.org/00g2tkw06","country_code":"US","type":"company","lineage":["https://openalex.org/I1292974536"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Dimitar Filev","raw_affiliation_strings":["Ford Motor Company,Dearborn,USA","Ford Motor Company, Dearborn, USA"],"affiliations":[{"raw_affiliation_string":"Ford Motor Company,Dearborn,USA","institution_ids":["https://openalex.org/I1292974536"]},{"raw_affiliation_string":"Ford Motor Company, Dearborn, USA","institution_ids":["https://openalex.org/I1292974536"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":8,"corresponding_author_ids":["https://openalex.org/A5006499382"],"corresponding_institution_ids":["https://openalex.org/I87216513"],"apc_list":null,"apc_paid":null,"fwci":0.6283,"has_fulltext":false,"cited_by_count":6,"citation_normalized_percentile":{"value":0.71845205,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":97},"biblio":{"volume":null,"issue":null,"first_page":"01","last_page":"08"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12761","display_name":"Data Stream Mining Techniques","score":0.9980000257492065,"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/T12761","display_name":"Data Stream Mining Techniques","score":0.9980000257492065,"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":0.9760000109672546,"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/T11326","display_name":"Stock Market Forecasting Methods","score":0.9666000008583069,"subfield":{"id":"https://openalex.org/subfields/1803","display_name":"Management Science and Operations Research"},"field":{"id":"https://openalex.org/fields/18","display_name":"Decision Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/interpretability","display_name":"Interpretability","score":0.845300555229187},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7847249507904053},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6903042793273926},{"id":"https://openalex.org/keywords/reinforcement-learning","display_name":"Reinforcement learning","score":0.6537588238716125},{"id":"https://openalex.org/keywords/decision-tree","display_name":"Decision tree","score":0.6258660554885864},{"id":"https://openalex.org/keywords/decipher","display_name":"DECIPHER","score":0.5556280612945557},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.5479346513748169},{"id":"https://openalex.org/keywords/state","display_name":"State (computer science)","score":0.48804154992103577},{"id":"https://openalex.org/keywords/tree","display_name":"Tree (set theory)","score":0.47342541813850403},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.4656895399093628},{"id":"https://openalex.org/keywords/action","display_name":"Action (physics)","score":0.45388513803482056},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.1289568543434143},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.10300624370574951}],"concepts":[{"id":"https://openalex.org/C2781067378","wikidata":"https://www.wikidata.org/wiki/Q17027399","display_name":"Interpretability","level":2,"score":0.845300555229187},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7847249507904053},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6903042793273926},{"id":"https://openalex.org/C97541855","wikidata":"https://www.wikidata.org/wiki/Q830687","display_name":"Reinforcement learning","level":2,"score":0.6537588238716125},{"id":"https://openalex.org/C84525736","wikidata":"https://www.wikidata.org/wiki/Q831366","display_name":"Decision tree","level":2,"score":0.6258660554885864},{"id":"https://openalex.org/C164614171","wikidata":"https://www.wikidata.org/wiki/Q5204775","display_name":"DECIPHER","level":2,"score":0.5556280612945557},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5479346513748169},{"id":"https://openalex.org/C48103436","wikidata":"https://www.wikidata.org/wiki/Q599031","display_name":"State (computer science)","level":2,"score":0.48804154992103577},{"id":"https://openalex.org/C113174947","wikidata":"https://www.wikidata.org/wiki/Q2859736","display_name":"Tree (set theory)","level":2,"score":0.47342541813850403},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.4656895399093628},{"id":"https://openalex.org/C2780791683","wikidata":"https://www.wikidata.org/wiki/Q846785","display_name":"Action (physics)","level":2,"score":0.45388513803482056},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.1289568543434143},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.10300624370574951},{"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/C54355233","wikidata":"https://www.wikidata.org/wiki/Q7162","display_name":"Genetics","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},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","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}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/ssci50451.2021.9659552","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ssci50451.2021.9659552","pdf_url":null,"source":{"id":"https://openalex.org/S4363604921","display_name":"2021 IEEE Symposium Series on Computational Intelligence (SSCI)","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":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 IEEE Symposium Series on Computational Intelligence (SSCI)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Peace, Justice and strong institutions","id":"https://metadata.un.org/sdg/16","score":0.7699999809265137}],"awards":[],"funders":[{"id":"https://openalex.org/F4320309637","display_name":"Mississippi State University","ror":"https://ror.org/0432jq872"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":20,"referenced_works":["https://openalex.org/W225560312","https://openalex.org/W1499669280","https://openalex.org/W1585546346","https://openalex.org/W1600437712","https://openalex.org/W2124175081","https://openalex.org/W2124357902","https://openalex.org/W2155968351","https://openalex.org/W2746553466","https://openalex.org/W2761873684","https://openalex.org/W2991448601","https://openalex.org/W3087163951","https://openalex.org/W3106710618","https://openalex.org/W4298857966","https://openalex.org/W6608886761","https://openalex.org/W6629881138","https://openalex.org/W6635147684","https://openalex.org/W6637967152","https://openalex.org/W6678114464","https://openalex.org/W6744838376","https://openalex.org/W6781626309"],"related_works":["https://openalex.org/W2115350162","https://openalex.org/W2905433371","https://openalex.org/W4361193272","https://openalex.org/W4310278675","https://openalex.org/W2806259446","https://openalex.org/W2963326959","https://openalex.org/W2330145053","https://openalex.org/W4247136043","https://openalex.org/W4312407344","https://openalex.org/W4293151273"],"abstract_inverted_index":{"The":[0,97,199],"recent":[1],"years":[2],"have":[3,182],"witnessed":[4],"a":[5,70,76,130,144,175,210,226],"surge":[6],"in":[7,164,168],"application":[8],"of":[9,32,94,99,121,125,139,174,185,194,218,231,233],"deep":[10],"neural":[11],"networks":[12],"(DNNs)":[13],"and":[14,24,37,74,132,166,171,192,239,245,254],"reinforcement":[15],"learning":[16,33,236],"(RL)":[17],"methods":[18],"to":[19,41,54,84,129,143,155,181,214,228,247],"various":[20,42],"autonomous":[21],"control":[22,148],"systems":[23],"game":[25],"playing":[26],"problems.":[27],"While":[28],"they":[29],"are":[30,103,179,204],"capable":[31,120],"from":[34,69],"real-world":[35],"data":[36,68],"produce":[38],"adequate":[39],"actions":[40],"state":[43],"conditions,":[44],"their":[45,59],"internal":[46],"complexity":[47,98],"does":[48],"not":[49],"allow":[50],"an":[51,56],"easy":[52],"way":[53],"provide":[55,215],"explanation":[57],"for":[58],"actions.":[60],"In":[61,108],"this":[62,150],"paper,":[63],"we":[64],"generate":[65],"state-action":[66,127],"pair":[67],"trained":[71],"DNN/RL":[72,95],"system":[73],"employ":[75],"previously":[77],"proposed":[78],"nonlinear":[79],"decision":[80,187,202],"tree":[81],"(NLDT)":[82],"framework":[83],"decipher":[85],"hidden":[86],"simplistic":[87,183],"rule":[88,101],"sets":[89,102],"that":[90,115],"interpret":[91],"the":[92,100,106,110,117,123,126,136,140,153,156,195,219,229,249],"working":[93,137],"systems.":[96],"controllable":[104],"by":[105,208],"user.":[107],"essence,":[109],"inherent":[111],"bilevel":[112],"optimization":[113],"procedure":[114],"finds":[116],"NLDTs":[118,178],"is":[119],"reducing":[122],"complexities":[124],"logic":[128],"minimalist":[131],"intrepretable":[133],"level.":[134],"Demonstrating":[135],"principle":[138],"NLDT":[141],"method":[142],"revised":[145],"mountain":[146],"car":[147],"problem,":[149],"paper":[151],"applies":[152],"methodology":[154],"lane":[157,220],"changing":[158],"problem":[159],"involving":[160,189],"six":[161,196],"critical":[162,197],"cars":[163],"front":[165],"rear":[167],"left,":[169],"middle,":[170],"right":[172],"lanes":[173],"pilot":[176],"car.":[177],"derived":[180,200],"relationships":[184],"12":[186],"variables":[188],"relative":[190],"distances":[191],"velocities":[193],"cars.":[198],"analytical":[201],"rules":[203],"then":[205],"simplified":[206],"further":[207,243],"using":[209],"symbolic":[211],"analysis":[212],"tool":[213],"English-like":[216],"interpretation":[217],"change":[221],"problem.":[222],"This":[223],"study":[224],"makes":[225],"scratch":[227],"issue":[230],"interpretability":[232],"modern":[234],"machine":[235],"based":[237],"tools":[238],"it":[240],"now":[241],"deserves":[242],"attention":[244],"applications":[246],"make":[248],"overall":[250],"approach":[251],"more":[252],"integrated":[253],"effective.":[255]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":4}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}