{"id":"https://openalex.org/W4417283694","doi":"https://doi.org/10.1145/3748636.3760463","title":"A Vision for Structured Experiential Mobility Intelligence","display_name":"A Vision for Structured Experiential Mobility Intelligence","publication_year":2025,"publication_date":"2025-11-03","ids":{"openalex":"https://openalex.org/W4417283694","doi":"https://doi.org/10.1145/3748636.3760463"},"language":null,"primary_location":{"id":"doi:10.1145/3748636.3760463","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3748636.3760463","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3748636.3760463","source":null,"license":"cc-by-nc-sa","license_id":"https://openalex.org/licenses/cc-by-nc-sa","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 33rd ACM International Conference on Advances in Geographic Information Systems","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/10.1145/3748636.3760463","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5008923918","display_name":"Manos Papagelis","orcid":"https://orcid.org/0000-0003-0138-2541"},"institutions":[{"id":"https://openalex.org/I192455969","display_name":"York University","ror":"https://ror.org/05fq50484","country_code":"CA","type":"education","lineage":["https://openalex.org/I192455969"]}],"countries":["CA"],"is_corresponding":true,"raw_author_name":"Manos Papagelis","raw_affiliation_strings":["Lassonde School of Engineering, York University, Ontario, Canada"],"raw_orcid":"https://orcid.org/0000-0003-0138-2541","affiliations":[{"raw_affiliation_string":"Lassonde School of Engineering, York University, Ontario, Canada","institution_ids":["https://openalex.org/I192455969"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5008923918"],"corresponding_institution_ids":["https://openalex.org/I192455969"],"apc_list":null,"apc_paid":null,"fwci":2.9894,"has_fulltext":true,"cited_by_count":2,"citation_normalized_percentile":{"value":0.91834736,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":97,"max":98},"biblio":{"volume":null,"issue":null,"first_page":"790","last_page":"794"},"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":0.24169999361038208,"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":0.24169999361038208,"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/T11896","display_name":"Opportunistic and Delay-Tolerant Networks","score":0.11620000004768372,"subfield":{"id":"https://openalex.org/subfields/1705","display_name":"Computer Networks and Communications"},"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/T11942","display_name":"Transportation and Mobility Innovations","score":0.08640000224113464,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/experiential-learning","display_name":"Experiential learning","score":0.7817000150680542},{"id":"https://openalex.org/keywords/generative-grammar","display_name":"Generative grammar","score":0.5374000072479248},{"id":"https://openalex.org/keywords/key","display_name":"Key (lock)","score":0.45559999346733093},{"id":"https://openalex.org/keywords/plan","display_name":"Plan (archaeology)","score":0.44589999318122864},{"id":"https://openalex.org/keywords/core","display_name":"Core (optical fiber)","score":0.40610000491142273},{"id":"https://openalex.org/keywords/foundation","display_name":"Foundation (evidence)","score":0.376800000667572},{"id":"https://openalex.org/keywords/generative-model","display_name":"Generative model","score":0.3612000048160553}],"concepts":[{"id":"https://openalex.org/C37228920","wikidata":"https://www.wikidata.org/wiki/Q1307600","display_name":"Experiential learning","level":2,"score":0.7817000150680542},{"id":"https://openalex.org/C39890363","wikidata":"https://www.wikidata.org/wiki/Q36108","display_name":"Generative grammar","level":2,"score":0.5374000072479248},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.483599990606308},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.45559999346733093},{"id":"https://openalex.org/C2776505523","wikidata":"https://www.wikidata.org/wiki/Q4785468","display_name":"Plan (archaeology)","level":2,"score":0.44589999318122864},{"id":"https://openalex.org/C2164484","wikidata":"https://www.wikidata.org/wiki/Q5170150","display_name":"Core (optical fiber)","level":2,"score":0.40610000491142273},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4050000011920929},{"id":"https://openalex.org/C2780966255","wikidata":"https://www.wikidata.org/wiki/Q5474306","display_name":"Foundation (evidence)","level":2,"score":0.376800000667572},{"id":"https://openalex.org/C167966045","wikidata":"https://www.wikidata.org/wiki/Q5532625","display_name":"Generative model","level":3,"score":0.3612000048160553},{"id":"https://openalex.org/C56739046","wikidata":"https://www.wikidata.org/wiki/Q192060","display_name":"Knowledge management","level":1,"score":0.36079999804496765},{"id":"https://openalex.org/C107457646","wikidata":"https://www.wikidata.org/wiki/Q207434","display_name":"Human\u2013computer interaction","level":1,"score":0.32829999923706055},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.3237000107765198},{"id":"https://openalex.org/C2522767166","wikidata":"https://www.wikidata.org/wiki/Q2374463","display_name":"Data science","level":1,"score":0.3215999901294708},{"id":"https://openalex.org/C75553542","wikidata":"https://www.wikidata.org/wiki/Q178161","display_name":"A priori and a posteriori","level":2,"score":0.31459999084472656},{"id":"https://openalex.org/C123353603","wikidata":"https://www.wikidata.org/wiki/Q5421070","display_name":"Experiential knowledge","level":2,"score":0.3089999854564667},{"id":"https://openalex.org/C539667460","wikidata":"https://www.wikidata.org/wiki/Q2414942","display_name":"Management science","level":1,"score":0.3075000047683716},{"id":"https://openalex.org/C183759332","wikidata":"https://www.wikidata.org/wiki/Q343680","display_name":"Action learning","level":4,"score":0.30000001192092896},{"id":"https://openalex.org/C188147891","wikidata":"https://www.wikidata.org/wiki/Q147638","display_name":"Cognitive science","level":1,"score":0.2874000072479248},{"id":"https://openalex.org/C97541855","wikidata":"https://www.wikidata.org/wiki/Q830687","display_name":"Reinforcement learning","level":2,"score":0.2808000147342682},{"id":"https://openalex.org/C22367795","wikidata":"https://www.wikidata.org/wiki/Q7625208","display_name":"Structured prediction","level":2,"score":0.2732999920845032},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.260699987411499},{"id":"https://openalex.org/C155911833","wikidata":"https://www.wikidata.org/wiki/Q3817354","display_name":"Spatial intelligence","level":2,"score":0.25110000371932983}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3748636.3760463","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3748636.3760463","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3748636.3760463","source":null,"license":"cc-by-nc-sa","license_id":"https://openalex.org/licenses/cc-by-nc-sa","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 33rd ACM International Conference on Advances in Geographic Information Systems","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.1145/3748636.3760463","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3748636.3760463","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3748636.3760463","source":null,"license":"cc-by-nc-sa","license_id":"https://openalex.org/licenses/cc-by-nc-sa","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 33rd ACM International Conference on Advances in Geographic Information Systems","raw_type":"proceedings-article"},"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320334593","display_name":"Natural Sciences and Engineering Research Council of Canada","ror":"https://ror.org/01h531d29"}],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4417283694.pdf","grobid_xml":"https://content.openalex.org/works/W4417283694.grobid-xml"},"referenced_works_count":4,"referenced_works":["https://openalex.org/W2788997482","https://openalex.org/W3133702157","https://openalex.org/W4387460511","https://openalex.org/W4409336685"],"related_works":[],"abstract_inverted_index":{"Current":[0],"AI":[1],"models":[2],"for":[3,22,41],"mobility":[4,67],"analytics,":[5],"built":[6],"on":[7],"static":[8],"datasets":[9],"and":[10,28,32,59,80,107,130],"generative":[11],"architectures,":[12],"are":[13,49],"reaching":[14],"their":[15],"limits.":[16],"They":[17],"often":[18],"fail":[19],"to":[20,73,99,111],"account":[21],"physical":[23],"constraints,":[24,79],"lack":[25],"long-term":[26],"memory,":[27],"struggle":[29],"with":[30,117],"reasoning":[31],"planning":[33],"in":[34,82],"dynamic":[35],"environments.":[36,64],"We":[37,93],"introduce":[38],"a":[39,96,127],"vision":[40,115],"Structured":[42],"Experiential":[43],"Mobility":[44],"Intelligence.":[45],"At":[46],"its":[47],"core":[48],"World":[50],"Foundation":[51],"Models":[52],"(WFMs),":[53],"which":[54],"capture":[55],"the":[56,108,124],"spatial,":[57],"temporal,":[58],"causal":[60],"structure":[61],"of":[62,126],"urban":[63],"WFMs":[65],"enable":[66],"agents,":[68],"through":[69,123],"stream-based":[70],"reinforcement":[71],"learning,":[72],"reason":[74],"about":[75],"causality,":[76],"plan":[77],"within":[78],"adapt":[81],"real":[83],"time":[84],"by":[85],"continuously":[86],"learning":[87],"from":[88],"realistic,":[89],"physically":[90],"grounded":[91],"interactions.":[92],"also":[94],"present":[95],"research":[97,105],"roadmap":[98],"advance":[100],"this":[101],"vision,":[102],"highlighting":[103],"key":[104],"questions":[106],"methodologies":[109],"needed":[110],"address":[112],"them.":[113],"Our":[114],"aligns":[116],"Kantian":[118],"epistemology,":[119],"where":[120],"knowledge":[121],"emerges":[122],"synthesis":[125],"priori":[128],"structures":[129],"experiential":[131],"learning.":[132]},"counts_by_year":[{"year":2026,"cited_by_count":2}],"updated_date":"2026-06-25T08:15:23.626066","created_date":"2025-12-12T00:00:00"}