{"id":"https://openalex.org/W2947858349","doi":"https://doi.org/10.1145/3316480.3322885","title":"Modeling Human Temporal Dynamics in Agent-Based Simulations","display_name":"Modeling Human Temporal Dynamics in Agent-Based Simulations","publication_year":2019,"publication_date":"2019-05-29","ids":{"openalex":"https://openalex.org/W2947858349","doi":"https://doi.org/10.1145/3316480.3322885","mag":"2947858349"},"language":"en","primary_location":{"id":"doi:10.1145/3316480.3322885","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3316480.3322885","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3316480.3322885","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2019 ACM SIGSIM Conference on Principles of Advanced Discrete Simulation","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/10.1145/3316480.3322885","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5016202883","display_name":"James Flamino","orcid":"https://orcid.org/0000-0002-2753-5481"},"institutions":[{"id":"https://openalex.org/I165799507","display_name":"Rensselaer Polytechnic Institute","ror":"https://ror.org/01rtyzb94","country_code":"US","type":"education","lineage":["https://openalex.org/I165799507"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"James Flamino","raw_affiliation_strings":["Rensselaer Polytechnic Institute, Troy, NY, USA"],"affiliations":[{"raw_affiliation_string":"Rensselaer Polytechnic Institute, Troy, NY, USA","institution_ids":["https://openalex.org/I165799507"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5063360531","display_name":"Weike Dai","orcid":null},"institutions":[{"id":"https://openalex.org/I165799507","display_name":"Rensselaer Polytechnic Institute","ror":"https://ror.org/01rtyzb94","country_code":"US","type":"education","lineage":["https://openalex.org/I165799507"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Weike Dai","raw_affiliation_strings":["Rensselaer Polytechnic Institute, Troy, NY, USA"],"affiliations":[{"raw_affiliation_string":"Rensselaer Polytechnic Institute, Troy, NY, USA","institution_ids":["https://openalex.org/I165799507"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5004745888","display_name":"Boles\u0142aw K. Szyma\u0144ski","orcid":"https://orcid.org/0000-0002-0307-6743"},"institutions":[{"id":"https://openalex.org/I165799507","display_name":"Rensselaer Polytechnic Institute","ror":"https://ror.org/01rtyzb94","country_code":"US","type":"education","lineage":["https://openalex.org/I165799507"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Boleslaw K. Szymanski","raw_affiliation_strings":["Rensselaer Polytechnic Institute, Troy, NY, USA"],"affiliations":[{"raw_affiliation_string":"Rensselaer Polytechnic Institute, Troy, NY, USA","institution_ids":["https://openalex.org/I165799507"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5016202883"],"corresponding_institution_ids":["https://openalex.org/I165799507"],"apc_list":null,"apc_paid":null,"fwci":0.7243,"has_fulltext":true,"cited_by_count":3,"citation_normalized_percentile":{"value":0.80354947,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":95},"biblio":{"volume":null,"issue":null,"first_page":"99","last_page":"102"},"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":0.9997000098228455,"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":0.9997000098228455,"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/T10698","display_name":"Transportation Planning and Optimization","score":0.9900000095367432,"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":0.9829999804496765,"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/computer-science","display_name":"Computer science","score":0.7808407545089722},{"id":"https://openalex.org/keywords/baseline","display_name":"Baseline (sea)","score":0.6450845003128052},{"id":"https://openalex.org/keywords/overhead","display_name":"Overhead (engineering)","score":0.4931480288505554},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.49291181564331055},{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.48905453085899353},{"id":"https://openalex.org/keywords/scale","display_name":"Scale (ratio)","score":0.47925829887390137},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.46912169456481934},{"id":"https://openalex.org/keywords/agent-based-model","display_name":"Agent-based model","score":0.458798348903656},{"id":"https://openalex.org/keywords/behavioral-pattern","display_name":"Behavioral pattern","score":0.4243015646934509},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.3650122880935669}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7808407545089722},{"id":"https://openalex.org/C12725497","wikidata":"https://www.wikidata.org/wiki/Q810247","display_name":"Baseline (sea)","level":2,"score":0.6450845003128052},{"id":"https://openalex.org/C2779960059","wikidata":"https://www.wikidata.org/wiki/Q7113681","display_name":"Overhead (engineering)","level":2,"score":0.4931480288505554},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.49291181564331055},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.48905453085899353},{"id":"https://openalex.org/C2778755073","wikidata":"https://www.wikidata.org/wiki/Q10858537","display_name":"Scale (ratio)","level":2,"score":0.47925829887390137},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.46912169456481934},{"id":"https://openalex.org/C2780873155","wikidata":"https://www.wikidata.org/wiki/Q392811","display_name":"Agent-based model","level":2,"score":0.458798348903656},{"id":"https://openalex.org/C83804111","wikidata":"https://www.wikidata.org/wiki/Q1063558","display_name":"Behavioral pattern","level":2,"score":0.4243015646934509},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3650122880935669},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0},{"id":"https://openalex.org/C111368507","wikidata":"https://www.wikidata.org/wiki/Q43518","display_name":"Oceanography","level":1,"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/C127313418","wikidata":"https://www.wikidata.org/wiki/Q1069","display_name":"Geology","level":0,"score":0.0},{"id":"https://openalex.org/C115903868","wikidata":"https://www.wikidata.org/wiki/Q80993","display_name":"Software engineering","level":1,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3316480.3322885","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3316480.3322885","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3316480.3322885","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2019 ACM SIGSIM Conference on Principles of Advanced Discrete Simulation","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.1145/3316480.3322885","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3316480.3322885","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3316480.3322885","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2019 ACM SIGSIM Conference on Principles of Advanced Discrete Simulation","raw_type":"proceedings-article"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G1198008555","display_name":null,"funder_award_id":"W911NF- 17-C-0099","funder_id":"https://openalex.org/F4320332180","funder_display_name":"Defense Advanced Research Projects Agency"},{"id":"https://openalex.org/G1987031270","display_name":null,"funder_award_id":"N00014-15-1-2640","funder_id":"https://openalex.org/F4320338295","funder_display_name":"Army Research Laboratory"},{"id":"https://openalex.org/G523448137","display_name":null,"funder_award_id":"W911NF-09-2-0053","funder_id":"https://openalex.org/F4320332180","funder_display_name":"Defense Advanced Research Projects Agency"},{"id":"https://openalex.org/G5259331294","display_name":null,"funder_award_id":"W911NF","funder_id":"https://openalex.org/F4320338295","funder_display_name":"Army Research Laboratory"},{"id":"https://openalex.org/G540615712","display_name":null,"funder_award_id":"N00014-15-1-2640","funder_id":"https://openalex.org/F4320337345","funder_display_name":"Office of Naval Research"},{"id":"https://openalex.org/G7931865478","display_name":null,"funder_award_id":"4-15-1-","funder_id":"https://openalex.org/F4320337345","funder_display_name":"Office of Naval Research"},{"id":"https://openalex.org/G8851674072","display_name":null,"funder_award_id":"W911NF-17-C-0099","funder_id":"https://openalex.org/F4320332180","funder_display_name":"Defense Advanced Research Projects Agency"},{"id":"https://openalex.org/G8876996369","display_name":null,"funder_award_id":"N00014","funder_id":"https://openalex.org/F4320337345","funder_display_name":"Office of Naval Research"},{"id":"https://openalex.org/G948678646","display_name":null,"funder_award_id":"W911NF-09-2-0053","funder_id":"https://openalex.org/F4320338295","funder_display_name":"Army Research Laboratory"},{"id":"https://openalex.org/G968430625","display_name":null,"funder_award_id":"N00014-15-1-2640","funder_id":"https://openalex.org/F4320338298","funder_display_name":"Office of Naval Research Global"}],"funders":[{"id":"https://openalex.org/F4320332180","display_name":"Defense Advanced Research Projects Agency","ror":"https://ror.org/02caytj08"},{"id":"https://openalex.org/F4320337345","display_name":"Office of Naval Research","ror":"https://ror.org/00rk2pe57"},{"id":"https://openalex.org/F4320338295","display_name":"Army Research Laboratory","ror":"https://ror.org/011hc8f90"},{"id":"https://openalex.org/F4320338298","display_name":"Office of Naval Research Global","ror":"https://ror.org/00rk2pe57"}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2947858349.pdf","grobid_xml":"https://content.openalex.org/works/W2947858349.grobid-xml"},"referenced_works_count":16,"referenced_works":["https://openalex.org/W34141764","https://openalex.org/W1849361375","https://openalex.org/W1965555277","https://openalex.org/W2021581601","https://openalex.org/W2078701302","https://openalex.org/W2080303295","https://openalex.org/W2112056172","https://openalex.org/W2130071305","https://openalex.org/W2137558058","https://openalex.org/W2146096861","https://openalex.org/W2166481425","https://openalex.org/W2914413202","https://openalex.org/W2951868921","https://openalex.org/W3177701684","https://openalex.org/W4253172700","https://openalex.org/W4255375128"],"related_works":["https://openalex.org/W2383111961","https://openalex.org/W2365952365","https://openalex.org/W2352448290","https://openalex.org/W2380820513","https://openalex.org/W2913146933","https://openalex.org/W2372385138","https://openalex.org/W4296359239","https://openalex.org/W2101155126","https://openalex.org/W2043093291","https://openalex.org/W2127108945"],"abstract_inverted_index":{"Time-based":[0],"habitual":[1],"behavior":[2,104],"is":[3],"exhibited":[4],"in":[5,27,86,111,115,121],"humans":[6],"globally.":[7],"Given":[8],"that":[9,44,56,97],"sleep":[10,25],"has":[11],"such":[12],"an":[13],"innate":[14],"influence":[15],"on":[16,102],"our":[17],"daily":[18],"activities,":[19],"modeling":[20],"the":[21,24,31,82,87,126],"patterns":[22,57,75],"of":[23,33,58,67,84],"cycle":[26],"order":[28],"to":[29,38,80,90,125],"understand":[30],"extent":[32],"its":[34],"impact":[35],"allows":[36],"us":[37],"also":[39,119],"capture":[40],"stable":[41],"behavioral":[42],"features":[43,100],"can":[45],"be":[46],"utilized":[47],"for":[48],"predictive":[49,92,122],"measures.":[50],"In":[51],"this":[52],"paper":[53],"we":[54,72],"show":[55],"temporal":[59],"preference":[60],"are":[61],"consistent":[62],"and":[63],"resilient":[64],"across":[65],"users":[66,85],"several":[68],"real-world":[69],"datasets.":[70],"Furthermore,":[71],"integrate":[73],"those":[74],"into":[76,105],"large-scale":[77],"agent-based":[78,106],"models":[79,107],"simulate":[81],"activity":[83],"involved":[88],"datasets":[89],"validate":[91],"accuracy.":[93],"Following":[94],"simulations":[95],"reveal":[96],"incorporating":[98],"clustering":[99],"based":[101],"time-based":[103],"not":[108],"only":[109],"result":[110,120],"a":[112],"significant":[113],"decrease":[114],"computational":[116],"overhead,":[117],"but":[118],"accuracy":[123],"comparable":[124],"baseline":[127],"models.":[128]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2021,"cited_by_count":1},{"year":2020,"cited_by_count":1}],"updated_date":"2026-04-21T08:09:41.155169","created_date":"2025-10-10T00:00:00"}