{"id":"https://openalex.org/W7224823762","doi":"https://doi.org/10.48550/arxiv.2610.38872","title":"Principal-agent hypothesis testing under adaptive experimentation","display_name":"Principal-agent hypothesis testing under adaptive experimentation","publication_year":2026,"publication_date":"2026-10-28","ids":{"openalex":"https://openalex.org/W7224823762","doi":"https://doi.org/10.48550/arxiv.2610.38872"},"language":"en","primary_location":{"id":"pmh:oai:arXiv.org:2610.38872","doi":null,"is_oa":true,"landing_page_url":"https://arxiv.org/abs/2610.38872","pdf_url":"https://arxiv.org/pdf/2610.38872","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":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"volume":null,"type":"preprint","indexed_in":["arxiv","datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2610.38872","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5026681234","display_name":"Ben Chugg","orcid":"https://orcid.org/0000-0003-1247-5428","observed_orcids":["https://orcid.org/0000-0003-1247-5428"]},"institutions":[{"id":"https://openalex.org/I74973139","display_name":"Carnegie Mellon University","ror":"https://ror.org/05x2bcf33","country_code":"US","type":"education","lineage":["https://openalex.org/I74973139"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Chugg, Ben","raw_affiliation_strings":["Carnegie Mellon University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Carnegie Mellon University","institution_ids":["https://openalex.org/I74973139"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100607334","display_name":"Aritra Ghosh","orcid":"https://orcid.org/0000-0003-2024-2173","observed_orcids":["https://orcid.org/0000-0003-2024-2173"]},"institutions":[{"id":"https://openalex.org/I6498739","display_name":"Indian Statistical Institute","ror":"https://ror.org/00q2w1j53","country_code":"IN","type":"education","lineage":["https://openalex.org/I6498739"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Ghosh, Aritra","raw_affiliation_strings":["Indian Statistical Institute"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Indian Statistical Institute","institution_ids":["https://openalex.org/I6498739"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5032389695","display_name":"Aaditya Ramdas","orcid":"https://orcid.org/0000-0003-0497-311X","observed_orcids":["https://orcid.org/0000-0003-0497-311X"]},"institutions":[{"id":"https://openalex.org/I97018004","display_name":"Stanford University","ror":"https://ror.org/00f54p054","country_code":"US","type":"education","lineage":["https://openalex.org/I97018004"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Ramdas, Aaditya","raw_affiliation_strings":["Stanford University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Stanford University","institution_ids":["https://openalex.org/I97018004"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":true,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11031","display_name":"Game Theory and Applications","score":0.6830999851226807,"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"}},"topics":[{"id":"https://openalex.org/T11031","display_name":"Game Theory and Applications","score":0.6830999851226807,"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"}},{"id":"https://openalex.org/T13500","display_name":"Probability and Statistical Research","score":0.0608999989926815,"subfield":{"id":"https://openalex.org/subfields/2613","display_name":"Statistics and Probability"},"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/T12101","display_name":"Advanced Bandit Algorithms Research","score":0.05920000001788139,"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/sequential-hypothesis-testing","display_name":"sequential hypothesis testing","score":0.7269999980926514},{"id":"https://openalex.org/keywords/adaptive-experimentation","display_name":"adaptive experimentation","score":0.7929999828338623},{"id":"https://openalex.org/keywords/e-processes","display_name":"e-processes","score":0.9869999885559082},{"id":"https://openalex.org/keywords/optimal-stopping-rule","display_name":"optimal stopping rule","score":0.7789999842643738},{"id":"https://openalex.org/keywords/snell-envelope","display_name":"Snell envelope","score":0.9900000095367432},{"id":"https://openalex.org/keywords/best-response","display_name":"best response","score":0.47600001096725464}],"concepts":[{"id":"https://openalex.org/C87007009","wikidata":"https://www.wikidata.org/wiki/Q210832","display_name":"Statistical hypothesis testing","level":2,"score":0.5534999966621399},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5221999883651733},{"id":"https://openalex.org/C191988596","wikidata":"https://www.wikidata.org/wiki/Q628374","display_name":"Null hypothesis","level":2,"score":0.49790000915527344},{"id":"https://openalex.org/C144559511","wikidata":"https://www.wikidata.org/wiki/Q2986279","display_name":"Principal (computer security)","level":2,"score":0.4562999904155731},{"id":"https://openalex.org/C181622380","wikidata":"https://www.wikidata.org/wiki/Q26911","display_name":"Profit (economics)","level":2,"score":0.414000004529953},{"id":"https://openalex.org/C120577422","wikidata":"https://www.wikidata.org/wiki/Q843558","display_name":"Alternative hypothesis","level":3,"score":0.39879998564720154},{"id":"https://openalex.org/C149782125","wikidata":"https://www.wikidata.org/wiki/Q160039","display_name":"Econometrics","level":1,"score":0.35429999232292175},{"id":"https://openalex.org/C5465570","wikidata":"https://www.wikidata.org/wiki/Q5326898","display_name":"Early stopping","level":3,"score":0.33009999990463257},{"id":"https://openalex.org/C110121322","wikidata":"https://www.wikidata.org/wiki/Q865811","display_name":"Distribution (mathematics)","level":2,"score":0.3287999927997589},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3264000117778778},{"id":"https://openalex.org/C149441793","wikidata":"https://www.wikidata.org/wiki/Q200726","display_name":"Probability distribution","level":2,"score":0.3208000063896179},{"id":"https://openalex.org/C144237770","wikidata":"https://www.wikidata.org/wiki/Q747534","display_name":"Mathematical economics","level":1,"score":0.3000999987125397},{"id":"https://openalex.org/C2993259228","wikidata":"https://www.wikidata.org/wiki/Q3320364","display_name":"Statistical evidence","level":3,"score":0.29409998655319214},{"id":"https://openalex.org/C80478641","wikidata":"https://www.wikidata.org/wiki/Q195771","display_name":"Sequential analysis","level":2,"score":0.28870001435279846},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.2838999927043915},{"id":"https://openalex.org/C200707436","wikidata":"https://www.wikidata.org/wiki/Q1053211","display_name":"Principal\u2013agent problem","level":3,"score":0.28360000252723694},{"id":"https://openalex.org/C34602496","wikidata":"https://www.wikidata.org/wiki/Q2271882","display_name":"Sequential probability ratio test","level":2,"score":0.2806999981403351},{"id":"https://openalex.org/C99888217","wikidata":"https://www.wikidata.org/wiki/Q1288707","display_name":"Stopping time","level":2,"score":0.27399998903274536},{"id":"https://openalex.org/C18762648","wikidata":"https://www.wikidata.org/wiki/Q42213","display_name":"Work (physics)","level":2,"score":0.25679999589920044}],"mesh":[],"locations_count":2,"locations":[{"id":"pmh:oai:arXiv.org:2610.38872","doi":null,"is_oa":true,"landing_page_url":"https://arxiv.org/abs/2610.38872","pdf_url":"https://arxiv.org/pdf/2610.38872","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":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},{"id":"doi:10.48550/arxiv.2610.38872","doi":"https://doi.org/10.48550/arxiv.2610.38872","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2610.38872","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":"pmh:oai:arXiv.org:2610.38872","doi":null,"is_oa":true,"landing_page_url":"https://arxiv.org/abs/2610.38872","pdf_url":"https://arxiv.org/pdf/2610.38872","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":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"sustainable_development_goals":[],"study_designs":[],"awards":[{"id":"https://openalex.org/G6012782794","display_name":"Game-theoretic statistics and safe anytime-valid inference","funder_award_id":"2310718","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G826810440","display_name":"AI Institute for Societal Decision Making (AI-SDM)","funder_award_id":"2229881","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"}],"funders":[{"id":"https://openalex.org/F4320306076","display_name":"National Science Foundation","ror":"https://ror.org/021nxhr62"}],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W7224823762.pdf","grobid_xml":"https://content.openalex.org/works/W7224823762.grobid-xml"},"referenced_works_count":0,"referenced_works":[],"related_works":["https://openalex.org/W7221787512","https://openalex.org/W7166648848","https://openalex.org/W2074490231","https://openalex.org/W2239438332","https://openalex.org/W4405765873","https://openalex.org/W4280649288","https://openalex.org/W4417324112","https://openalex.org/W4412638226","https://openalex.org/W4289285935","https://openalex.org/W7203440994"],"abstract_inverted_index":{"Principal-agent":[0],"hypothesis":[1],"testing":[2],"studies":[3],"statistical":[4],"contracts":[5,102],"in":[6,82,88],"which":[7],"a":[8,30,63,70],"principal":[9],"rewards":[10,45],"an":[11],"agent":[12,17,28,57,139],"according":[13],"to":[14,37,49,110,140],"data":[15],"the":[16,23,27,35,50,56,60,83,111,117,122,126,138],"generates.":[18],"Existing":[19],"work":[20],"focuses":[21],"on":[22],"single-shot":[24],"setting,":[25],"where":[26,40],"produces":[29],"single":[31],"dataset.":[32],"We":[33,68,107,129],"extend":[34],"framework":[36],"sequential":[38],"settings,":[39],"evidence":[41],"accumulates":[42],"over":[43],"time,":[44],"may":[46,58],"be":[47],"deferred":[48],"end":[51],"or":[52],"disbursed":[53],"incrementally,":[54],"and":[55,94,115],"stop":[59],"contract":[61,71],"at":[62],"strategically":[64],"chosen":[65],"stopping":[66,92,119],"time.":[67],"call":[69],"null-deterring":[72],"if":[73],"no":[74],"''null":[75],"agent''":[76],"(those":[77],"whose":[78],"data-generating":[79],"distribution":[80],"lies":[81],"null":[84],"hypothesis)":[85],"can":[86],"profit":[87],"expectation":[89],"under":[90],"any":[91],"rule,":[93],"our":[95],"main":[96],"conceptual":[97],"result":[98],"shows":[99],"that":[100,135],"such":[101],"are":[103],"characterized":[104],"by":[105],"e-processes.":[106],"then":[108],"turn":[109],"agent's":[112],"best":[113],"response":[114],"identify":[116],"optimal":[118],"rule":[120],"through":[121],"Snell":[123],"envelope":[124],"of":[125,145],"reward":[127],"process.":[128],"develop":[130],"simpler,":[131],"more":[132],"interpretable":[133],"approximations":[134],"often":[136],"require":[137],"have":[141],"only":[142],"partial":[143],"knowledge":[144],"its":[146],"distribution.":[147]},"counts_by_year":[],"updated_date":"2026-11-03T10:50:19.383937","created_date":"2026-10-31T00:00:00"}
