{"id":"https://openalex.org/W2985448248","doi":"https://doi.org/10.1145/3356471.3365229","title":"Imitation Learning from Human-Generated Spatial-Temporal Data","display_name":"Imitation Learning from Human-Generated Spatial-Temporal Data","publication_year":2019,"publication_date":"2019-11-01","ids":{"openalex":"https://openalex.org/W2985448248","doi":"https://doi.org/10.1145/3356471.3365229","mag":"2985448248"},"language":"en","primary_location":{"id":"doi:10.1145/3356471.3365229","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3356471.3365229","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3356471.3365229","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 3rd ACM SIGSPATIAL International Workshop on AI for Geographic Knowledge Discovery","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://dl.acm.org/doi/pdf/10.1145/3356471.3365229","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5100630059","display_name":"Yanhua Li","orcid":"https://orcid.org/0000-0001-8972-503X"},"institutions":[{"id":"https://openalex.org/I107077323","display_name":"Worcester Polytechnic Institute","ror":"https://ror.org/05ejpqr48","country_code":"US","type":"education","lineage":["https://openalex.org/I107077323"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Yanhua Li","raw_affiliation_strings":["Worcester Polytechnic Institute"],"affiliations":[{"raw_affiliation_string":"Worcester Polytechnic Institute","institution_ids":["https://openalex.org/I107077323"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5013900180","display_name":"Weixiao Huang","orcid":null},"institutions":[{"id":"https://openalex.org/I107077323","display_name":"Worcester Polytechnic Institute","ror":"https://ror.org/05ejpqr48","country_code":"US","type":"education","lineage":["https://openalex.org/I107077323"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Weixiao Huang","raw_affiliation_strings":["Worcester Polytechnic Institute"],"affiliations":[{"raw_affiliation_string":"Worcester Polytechnic Institute","institution_ids":["https://openalex.org/I107077323"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5100630059"],"corresponding_institution_ids":["https://openalex.org/I107077323"],"apc_list":null,"apc_paid":null,"fwci":1.0862,"has_fulltext":true,"cited_by_count":3,"citation_normalized_percentile":{"value":0.84081499,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":94},"biblio":{"volume":"201","issue":null,"first_page":"9","last_page":"10"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11980","display_name":"Human Mobility and Location-Based Analysis","score":0.9958999752998352,"subfield":{"id":"https://openalex.org/subfields/3313","display_name":"Transportation"},"field":{"id":"https://openalex.org/fields/33","display_name":"Social Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},"topics":[{"id":"https://openalex.org/T11980","display_name":"Human Mobility and Location-Based Analysis","score":0.9958999752998352,"subfield":{"id":"https://openalex.org/subfields/3313","display_name":"Transportation"},"field":{"id":"https://openalex.org/fields/33","display_name":"Social Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T11942","display_name":"Transportation and Mobility Innovations","score":0.9943000078201294,"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/T10298","display_name":"Urban Transport and Accessibility","score":0.991100013256073,"subfield":{"id":"https://openalex.org/subfields/3313","display_name":"Transportation"},"field":{"id":"https://openalex.org/fields/33","display_name":"Social Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/imitation","display_name":"Imitation","score":0.7852838039398193},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7362619042396545},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5287801027297974},{"id":"https://openalex.org/keywords/spatial-analysis","display_name":"Spatial analysis","score":0.454036682844162},{"id":"https://openalex.org/keywords/data-science","display_name":"Data science","score":0.425202876329422},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.37957465648651123},{"id":"https://openalex.org/keywords/human\u2013computer-interaction","display_name":"Human\u2013computer interaction","score":0.3592374920845032},{"id":"https://openalex.org/keywords/geography","display_name":"Geography","score":0.12129765748977661},{"id":"https://openalex.org/keywords/psychology","display_name":"Psychology","score":0.0882224440574646}],"concepts":[{"id":"https://openalex.org/C126388530","wikidata":"https://www.wikidata.org/wiki/Q1131737","display_name":"Imitation","level":2,"score":0.7852838039398193},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7362619042396545},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5287801027297974},{"id":"https://openalex.org/C159620131","wikidata":"https://www.wikidata.org/wiki/Q1938983","display_name":"Spatial analysis","level":2,"score":0.454036682844162},{"id":"https://openalex.org/C2522767166","wikidata":"https://www.wikidata.org/wiki/Q2374463","display_name":"Data science","level":1,"score":0.425202876329422},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.37957465648651123},{"id":"https://openalex.org/C107457646","wikidata":"https://www.wikidata.org/wiki/Q207434","display_name":"Human\u2013computer interaction","level":1,"score":0.3592374920845032},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.12129765748977661},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.0882224440574646},{"id":"https://openalex.org/C77805123","wikidata":"https://www.wikidata.org/wiki/Q161272","display_name":"Social psychology","level":1,"score":0.0},{"id":"https://openalex.org/C62649853","wikidata":"https://www.wikidata.org/wiki/Q199687","display_name":"Remote sensing","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3356471.3365229","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3356471.3365229","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3356471.3365229","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 3rd ACM SIGSPATIAL International Workshop on AI for Geographic Knowledge Discovery","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.1145/3356471.3365229","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3356471.3365229","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3356471.3365229","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 3rd ACM SIGSPATIAL International Workshop on AI for Geographic Knowledge Discovery","raw_type":"proceedings-article"},"sustainable_development_goals":[{"display_name":"Sustainable cities and communities","id":"https://metadata.un.org/sdg/11","score":0.6100000143051147}],"awards":[{"id":"https://openalex.org/G1097636904","display_name":null,"funder_award_id":"CNS-1657350, CMMI-1831140","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G1668733529","display_name":null,"funder_award_id":"CNS-1657350","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G3809593559","display_name":null,"funder_award_id":"CMMI-1831140","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G5252722770","display_name":"CRII: CPS: CityLines: Designing Urban Hub-and-Spoke Transportation System with Data-Driven Cyber-Control","funder_award_id":"1657350","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G5954070948","display_name":null,"funder_award_id":"CMMI-","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G8372766862","display_name":"SCC: Leveraging Autonomous Shared Vehicles for Greater Community Health, Equity, Livability, and Prosperity (HELP)","funder_award_id":"1831140","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G8761899520","display_name":null,"funder_award_id":"1831140","funder_id":"https://openalex.org/F4320337391","funder_display_name":"Division of Civil, Mechanical and Manufacturing Innovation"}],"funders":[{"id":"https://openalex.org/F4320306076","display_name":"National Science Foundation","ror":"https://ror.org/021nxhr62"},{"id":"https://openalex.org/F4320337391","display_name":"Division of Civil, Mechanical and Manufacturing Innovation","ror":"https://ror.org/028yd4c30"}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2985448248.pdf","grobid_xml":"https://content.openalex.org/works/W2985448248.grobid-xml"},"referenced_works_count":16,"referenced_works":["https://openalex.org/W102110531","https://openalex.org/W1999874108","https://openalex.org/W2098774185","https://openalex.org/W2109675615","https://openalex.org/W2113023245","https://openalex.org/W2133068870","https://openalex.org/W2171114620","https://openalex.org/W2290104316","https://openalex.org/W2434014514","https://openalex.org/W2604455040","https://openalex.org/W2907455543","https://openalex.org/W2914112028","https://openalex.org/W2944211469","https://openalex.org/W3003540860","https://openalex.org/W3010996978","https://openalex.org/W3013077068"],"related_works":["https://openalex.org/W4387497383","https://openalex.org/W3183948672","https://openalex.org/W3173606202","https://openalex.org/W3110381201","https://openalex.org/W2948807893","https://openalex.org/W2935909890","https://openalex.org/W2778153218","https://openalex.org/W2758277628","https://openalex.org/W1531601525","https://openalex.org/W2665305151"],"abstract_inverted_index":{"Human":[0],"dwellers":[1],"make":[2],"daily":[3],"decisions":[4],"by":[5],"their":[6,10,46],"own":[7],"\"strategies\"":[8],"governing":[9],"mobility":[11],"dynamics":[12],"(e.g.,":[13],"Uber":[14],"drivers":[15],"have":[16,25],"preferred":[17,26],"working":[18],"regions":[19],"and":[20,22,28,32,64,72,88,105],"times,":[21],"urban":[23],"commuters":[24],"routes":[27],"transit":[29],"modes).":[30],"Understanding":[31],"characterizing":[33],"the":[34,66,83,89,107],"unique":[35],"decision-making":[36,75],"strategies":[37,76],"of":[38,70,91],"human":[39,74],"agents":[40],"has":[41],"great":[42],"potential":[43],"in":[44,94],"promoting":[45],"individual":[47],"well-being.":[48],"In":[49],"this":[50],"paper,":[51],"we":[52,100],"outline":[53,106],"a":[54],"novel":[55],"spatial-temporal":[56,79,97],"imitation":[57,85],"learning":[58,73,86],"(STIL)":[59],"framework":[60],"that":[61],"defines,":[62],"investigates,":[63],"addresses":[65],"emerging":[67],"research":[68],"challenges":[69],"analyzing":[71,95],"from":[77],"human-generated":[78,96],"data.":[80,98],"We":[81],"present":[82,101],"state-of-the-art":[84],"algorithms,":[87],"limitations":[90],"these":[92],"algorithms":[93],"Moreover,":[99],"our":[102],"preliminary":[103],"studies,":[104],"challenging":[108],"open":[109],"questions.":[110]},"counts_by_year":[{"year":2021,"cited_by_count":1},{"year":2020,"cited_by_count":1},{"year":2019,"cited_by_count":1}],"updated_date":"2026-04-10T15:06:20.359241","created_date":"2025-10-10T00:00:00"}