{"id":"https://openalex.org/W4385764091","doi":"https://doi.org/10.24963/ijcai.2023/682","title":"Planning Multiple Epidemic Interventions with Reinforcement Learning","display_name":"Planning Multiple Epidemic Interventions with Reinforcement Learning","publication_year":2023,"publication_date":"2023-08-01","ids":{"openalex":"https://openalex.org/W4385764091","doi":"https://doi.org/10.24963/ijcai.2023/682"},"language":"en","primary_location":{"id":"doi:10.24963/ijcai.2023/682","doi":"https://doi.org/10.24963/ijcai.2023/682","is_oa":true,"landing_page_url":"http://dx.doi.org/10.24963/ijcai.2023/682","pdf_url":"https://www.ijcai.org/proceedings/2023/0682.pdf","source":{"id":"https://openalex.org/S4306419999","display_name":"International Joint Conference on Artificial Intelligence","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"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":"Proceedings of the Thirty-Second International Joint Conference on Artificial Intelligence","raw_type":"proceedings-article"},"volume":null,"type":"conference-paper","is_traditional":true,"indexed_in":["arxiv","crossref","datacite"],"open_access":{"is_oa":true,"oa_status":"bronze","oa_url":"https://www.ijcai.org/proceedings/2023/0682.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5058307425","display_name":"Anh Mai","orcid":"https://orcid.org/0009-0002-9604-7163","observed_orcids":["https://orcid.org/0009-0002-9604-7163"]},"institutions":[{"id":"https://openalex.org/I120250893","display_name":"New York University Abu Dhabi","ror":"https://ror.org/00e5k0821","country_code":"AE","type":"education","lineage":["https://openalex.org/I120250893","https://openalex.org/I57206974"]}],"countries":["AE"],"is_corresponding":false,"raw_author_name":"Anh Mai","raw_affiliation_strings":["New York University Abu Dhabi"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"New York University Abu Dhabi","institution_ids":["https://openalex.org/I120250893"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100311114","display_name":"Nikunj Gupta","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I57206974","display_name":"New York University","ror":"https://ror.org/0190ak572","country_code":"US","type":"education","lineage":["https://openalex.org/I57206974"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Nikunj Gupta","raw_affiliation_strings":["New York University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"New York University","institution_ids":["https://openalex.org/I57206974"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5044418740","display_name":"Azza Abouzied","orcid":"https://orcid.org/0000-0003-4273-2536","observed_orcids":["https://orcid.org/0000-0003-4273-2536"]},"institutions":[{"id":"https://openalex.org/I120250893","display_name":"New York University Abu Dhabi","ror":"https://ror.org/00e5k0821","country_code":"AE","type":"education","lineage":["https://openalex.org/I120250893","https://openalex.org/I57206974"]}],"countries":["AE"],"is_corresponding":false,"raw_author_name":"Azza Abouzied","raw_affiliation_strings":["New York University Abu Dhabi"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"New York University Abu Dhabi","institution_ids":["https://openalex.org/I120250893"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5055576104","display_name":"Dennis E. Shasha","orcid":"https://orcid.org/0000-0002-7036-3312","observed_orcids":["https://orcid.org/0000-0002-7036-3312"]},"institutions":[{"id":"https://openalex.org/I57206974","display_name":"New York University","ror":"https://ror.org/0190ak572","country_code":"US","type":"education","lineage":["https://openalex.org/I57206974"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Dennis Shasha","raw_affiliation_strings":["New York University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"New York University","institution_ids":["https://openalex.org/I57206974"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.8838,"has_fulltext":true,"cited_by_count":8,"citation_normalized_percentile":{"value":0.78331645,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":96,"max":98},"biblio":{"volume":null,"issue":null,"first_page":"6147","last_page":"6155"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10462","display_name":"Reinforcement Learning in Robotics","score":0.6567000150680542,"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/T10462","display_name":"Reinforcement Learning in Robotics","score":0.6567000150680542,"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/T10410","display_name":"COVID-19 epidemiological studies","score":0.11879999935626984,"subfield":{"id":"https://openalex.org/subfields/2611","display_name":"Modeling and Simulation"},"field":{"id":"https://openalex.org/fields/26","display_name":"Mathematics"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10482","display_name":"Mathematical and Theoretical Epidemiology and Ecology Models","score":0.07010000199079514,"subfield":{"id":"https://openalex.org/subfields/2604","display_name":"Applied Mathematics"},"field":{"id":"https://openalex.org/fields/26","display_name":"Mathematics"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/epidemic-control","display_name":"epidemic control","score":0.4259999990463257},{"id":"https://openalex.org/keywords/markov-decision-process","display_name":"Markov decision process","score":0.8949999809265137},{"id":"https://openalex.org/keywords/actor-critic-reinforcement-learning","display_name":"actor-critic reinforcement learning","score":0.8610000014305115},{"id":"https://openalex.org/keywords/proximal-policy-optimization","display_name":"proximal policy optimization","score":0.8410000205039978},{"id":"https://openalex.org/keywords/soft-actor-critic","display_name":"soft actor-critic","score":0.9860000014305115},{"id":"https://openalex.org/keywords/economic-cost-minimization","display_name":"economic cost minimization","score":0.6430000066757202},{"id":"https://openalex.org/keywords/public-health-policy","display_name":"public health policy","score":0.6019999980926514},{"id":"https://openalex.org/keywords/mask-mandates","display_name":"mask mandates","score":0.4580000042915344},{"id":"https://openalex.org/keywords/school-closures","display_name":"school closures","score":0.593999981880188},{"id":"https://openalex.org/keywords/vaccination","display_name":"vaccination","score":0.7630000114440918}],"concepts":[{"id":"https://openalex.org/C97541855","wikidata":"https://www.wikidata.org/wiki/Q830687","display_name":"Reinforcement learning","level":2,"score":0.8242393136024475},{"id":"https://openalex.org/C106189395","wikidata":"https://www.wikidata.org/wiki/Q176789","display_name":"Markov decision process","level":3,"score":0.7859959602355957},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6727105975151062},{"id":"https://openalex.org/C27415008","wikidata":"https://www.wikidata.org/wiki/Q7256382","display_name":"Psychological intervention","level":2,"score":0.6652625203132629},{"id":"https://openalex.org/C72434380","wikidata":"https://www.wikidata.org/wiki/Q230930","display_name":"State space","level":2,"score":0.5494085550308228},{"id":"https://openalex.org/C2776505523","wikidata":"https://www.wikidata.org/wiki/Q4785468","display_name":"Plan (archaeology)","level":2,"score":0.49820923805236816},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.45461970567703247},{"id":"https://openalex.org/C159886148","wikidata":"https://www.wikidata.org/wiki/Q176645","display_name":"Markov process","level":2,"score":0.4497426152229309},{"id":"https://openalex.org/C2778572836","wikidata":"https://www.wikidata.org/wiki/Q380933","display_name":"Space (punctuation)","level":2,"score":0.44294852018356323},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.3797411024570465},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.36911541223526},{"id":"https://openalex.org/C539667460","wikidata":"https://www.wikidata.org/wiki/Q2414942","display_name":"Management science","level":1,"score":0.36507484316825867},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.35033783316612244},{"id":"https://openalex.org/C112930515","wikidata":"https://www.wikidata.org/wiki/Q4389547","display_name":"Risk analysis (engineering)","level":1,"score":0.34493696689605713},{"id":"https://openalex.org/C42475967","wikidata":"https://www.wikidata.org/wiki/Q194292","display_name":"Operations research","level":1,"score":0.34161576628685},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.11114278435707092},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.10963556170463562},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.09792429208755493},{"id":"https://openalex.org/C166957645","wikidata":"https://www.wikidata.org/wiki/Q23498","display_name":"Archaeology","level":1,"score":0.0},{"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/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.0},{"id":"https://openalex.org/C95457728","wikidata":"https://www.wikidata.org/wiki/Q309","display_name":"History","level":0,"score":0.0},{"id":"https://openalex.org/C118552586","wikidata":"https://www.wikidata.org/wiki/Q7867","display_name":"Psychiatry","level":1,"score":0.0}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.24963/ijcai.2023/682","doi":"https://doi.org/10.24963/ijcai.2023/682","is_oa":true,"landing_page_url":"http://dx.doi.org/10.24963/ijcai.2023/682","pdf_url":"https://www.ijcai.org/proceedings/2023/0682.pdf","source":{"id":"https://openalex.org/S4306419999","display_name":"International Joint Conference on Artificial Intelligence","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"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":"Proceedings of the Thirty-Second International Joint Conference on Artificial Intelligence","raw_type":"proceedings-article"},{"id":"pmh:oai:arXiv.org:2301.12802","doi":null,"is_oa":true,"landing_page_url":"http://arxiv.org/abs/2301.12802","pdf_url":"https://arxiv.org/pdf/2301.12802","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,"listed_in":[],"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":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},{"id":"doi:10.48550/arxiv.2301.12802","doi":"https://doi.org/10.48550/arxiv.2301.12802","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2301.12802","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,"listed_in":[],"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"}],"best_oa_location":{"id":"doi:10.24963/ijcai.2023/682","doi":"https://doi.org/10.24963/ijcai.2023/682","is_oa":true,"landing_page_url":"http://dx.doi.org/10.24963/ijcai.2023/682","pdf_url":"https://www.ijcai.org/proceedings/2023/0682.pdf","source":{"id":"https://openalex.org/S4306419999","display_name":"International Joint Conference on Artificial Intelligence","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"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":"Proceedings of the Thirty-Second International Joint Conference on Artificial Intelligence","raw_type":"proceedings-article"},"sustainable_development_goals":[{"display_name":"Good health and well-being","score":0.5683000087738037,"id":"https://metadata.un.org/sdg/3"}],"study_designs":[],"awards":[{"id":"https://openalex.org/G3288531224","display_name":null,"funder_award_id":"CG001","funder_id":"https://openalex.org/F4320330069","funder_display_name":"Tamkeen"},{"id":"https://openalex.org/G8833531855","display_name":null,"funder_award_id":"CG001","funder_id":"https://openalex.org/F4320313203","funder_display_name":"New York University Abu Dhabi"}],"funders":[{"id":"https://openalex.org/F4320313203","display_name":"New York University Abu Dhabi","ror":"https://ror.org/00e5k0821"},{"id":"https://openalex.org/F4320330069","display_name":"Tamkeen","ror":"https://ror.org/00bqpz325"}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4385764091.pdf","grobid_xml":"https://content.openalex.org/works/W4385764091.grobid-xml"},"referenced_works_count":40,"referenced_works":["https://openalex.org/W1625390266","https://openalex.org/W1984773015","https://openalex.org/W2082028420","https://openalex.org/W2149935468","https://openalex.org/W2156737235","https://openalex.org/W2168024904","https://openalex.org/W2736601468","https://openalex.org/W2781726626","https://openalex.org/W2921376859","https://openalex.org/W2953708620","https://openalex.org/W3014396143","https://openalex.org/W3018485220","https://openalex.org/W3022013395","https://openalex.org/W3023200214","https://openalex.org/W3023721945","https://openalex.org/W3035700320","https://openalex.org/W3044688128","https://openalex.org/W3047392163","https://openalex.org/W3082144192","https://openalex.org/W3084213548","https://openalex.org/W3092007362","https://openalex.org/W3112853524","https://openalex.org/W3135257712","https://openalex.org/W3159596580","https://openalex.org/W3161096839","https://openalex.org/W3182322007","https://openalex.org/W3198940765","https://openalex.org/W3205880672","https://openalex.org/W3216772467","https://openalex.org/W4200048221","https://openalex.org/W4200635518","https://openalex.org/W4210258782","https://openalex.org/W4210886675","https://openalex.org/W4220882107","https://openalex.org/W4285820366","https://openalex.org/W4290927928","https://openalex.org/W4292596058","https://openalex.org/W4297218033","https://openalex.org/W4306822038","https://openalex.org/W4311204468"],"related_works":["https://openalex.org/W3174205737","https://openalex.org/W3083778362","https://openalex.org/W7106648713","https://openalex.org/W3092007362","https://openalex.org/W3166754645","https://openalex.org/W4285168339","https://openalex.org/W3035804808","https://openalex.org/W7163916109","https://openalex.org/W3014396143","https://openalex.org/W4387216693"],"abstract_inverted_index":{"Combating":[0],"an":[1,30,43,47],"epidemic":[2,31],"entails":[3],"finding":[4],"a":[5,80,87,99,178],"plan":[6,27,45],"that":[7,61,67,142,162],"describes":[8],"when":[9,74],"and":[10,39,70,82,89,136,155],"how":[11,126],"to":[12,110,127,138,159,181],"apply":[13,129],"different":[14],"interventions,":[15],"such":[16],"as":[17,98],"mask-wearing":[18],"mandates,":[19],"vaccinations,":[20],"school":[21],"or":[22],"workplace":[23],"closures.":[24],"An":[25],"optimal":[26,44],"will":[28],"curb":[29],"with":[32],"minimal":[33],"loss":[34],"of":[35,152,177],"life,":[36],"disease":[37,69,117],"burden,":[38],"economic":[40,71],"cost.":[41],"Finding":[42],"is":[46,105],"intractable":[48],"computational":[49,179],"problem":[50,97],"in":[51,107],"realistic":[52],"settings.":[53],"Policy-makers,":[54],"however,":[55],"would":[56],"greatly":[57],"benefit":[58],"from":[59],"tools":[60],"can":[62],"efficiently":[63],"search":[64,139],"for":[65,140],"plans":[66,141,164],"minimize":[68,143],"costs":[72],"especially":[73],"considering":[75],"multiple":[76,112],"possible":[77],"interventions":[78,114],"over":[79,115],"continuous":[81,88,113],"complex":[83,91],"action":[84],"space":[85],"given":[86],"equally":[90],"state":[92],"space.":[93],"We":[94,124,146],"formulate":[95],"this":[96],"Markov":[100],"decision":[101],"process.":[102],"Our":[103,168,172],"formulation":[104],"unique":[106],"its":[108],"ability":[109],"represent":[111],"any":[116],"model":[118],"defined":[119],"by":[120,166],"ordinary":[121],"differential":[122],"equations.":[123],"illustrate":[125],"effectively":[128],"state-of-the-art":[130],"actor-critic":[131],"reinforcement":[132],"learning":[133,150],"algorithms":[134,154],"(PPO":[135],"SAC)":[137],"overall":[144],"costs.":[145],"empirically":[147],"evaluate":[148],"the":[149,175],"performance":[151,158],"these":[153],"compare":[156],"their":[157],"hand-crafted":[160],"baselines":[161],"mimic":[163],"constructed":[165],"policy-makers.":[167,183],"method":[169],"outperforms":[170],"baselines.":[171],"work":[173],"confirms":[174],"viability":[176],"approach":[180],"support":[182]},"counts_by_year":[{"year":2026,"cited_by_count":3},{"year":2025,"cited_by_count":5}],"updated_date":"2026-11-07T11:25:07.637180","created_date":"2023-08-12T00:00:00"}