{"id":"https://openalex.org/W7161976347","doi":"https://doi.org/10.48550/arxiv.2605.21458","title":"Mind the Sim-to-Real Gap & Think Like a Scientist","display_name":"Mind the Sim-to-Real Gap & Think Like a Scientist","publication_year":2026,"publication_date":"2026-05-20","ids":{"openalex":"https://openalex.org/W7161976347","doi":"https://doi.org/10.48550/arxiv.2605.21458"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2605.21458","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.21458","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"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"},"type":"preprint","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.48550/arxiv.2605.21458","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5136642949","display_name":"Harsh Parikh","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Parikh, Harsh","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5040104942","display_name":"Gabriel Levin-Konigsberg","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Levin-Konigsberg, Gabriel","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5136231818","display_name":"Dominique Perrault-Joncas","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Perrault-Joncas, Dominique","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5056559023","display_name":"Alexander Volfovsky","orcid":"https://orcid.org/0000-0003-4462-1020"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Volfovsky, Alexander","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"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/T12101","display_name":"Advanced Bandit Algorithms Research","score":0.21449999511241913,"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/T12101","display_name":"Advanced Bandit Algorithms Research","score":0.21449999511241913,"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/T10462","display_name":"Reinforcement Learning in Robotics","score":0.15080000460147858,"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/T11195","display_name":"Simulation Techniques and Applications","score":0.14810000360012054,"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/reachability","display_name":"Reachability","score":0.6901999711990356},{"id":"https://openalex.org/keywords/bounded-function","display_name":"Bounded function","score":0.5321999788284302},{"id":"https://openalex.org/keywords/calibration","display_name":"Calibration","score":0.5041000247001648},{"id":"https://openalex.org/keywords/parametric-statistics","display_name":"Parametric statistics","score":0.5030999779701233},{"id":"https://openalex.org/keywords/lemma","display_name":"Lemma (botany)","score":0.4918000102043152},{"id":"https://openalex.org/keywords/value","display_name":"Value (mathematics)","score":0.47269999980926514},{"id":"https://openalex.org/keywords/variance","display_name":"Variance (accounting)","score":0.4713999927043915},{"id":"https://openalex.org/keywords/trimming","display_name":"Trimming","score":0.44609999656677246},{"id":"https://openalex.org/keywords/markov-decision-process","display_name":"Markov decision process","score":0.41280001401901245}],"concepts":[{"id":"https://openalex.org/C136643341","wikidata":"https://www.wikidata.org/wiki/Q1361526","display_name":"Reachability","level":2,"score":0.6901999711990356},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5353999733924866},{"id":"https://openalex.org/C34388435","wikidata":"https://www.wikidata.org/wiki/Q2267362","display_name":"Bounded function","level":2,"score":0.5321999788284302},{"id":"https://openalex.org/C165838908","wikidata":"https://www.wikidata.org/wiki/Q736777","display_name":"Calibration","level":2,"score":0.5041000247001648},{"id":"https://openalex.org/C117251300","wikidata":"https://www.wikidata.org/wiki/Q1849855","display_name":"Parametric statistics","level":2,"score":0.5030999779701233},{"id":"https://openalex.org/C2777759810","wikidata":"https://www.wikidata.org/wiki/Q149316","display_name":"Lemma (botany)","level":3,"score":0.4918000102043152},{"id":"https://openalex.org/C2776291640","wikidata":"https://www.wikidata.org/wiki/Q2912517","display_name":"Value (mathematics)","level":2,"score":0.47269999980926514},{"id":"https://openalex.org/C196083921","wikidata":"https://www.wikidata.org/wiki/Q7915758","display_name":"Variance (accounting)","level":2,"score":0.4713999927043915},{"id":"https://openalex.org/C56951928","wikidata":"https://www.wikidata.org/wiki/Q3539213","display_name":"Trimming","level":2,"score":0.44609999656677246},{"id":"https://openalex.org/C106189395","wikidata":"https://www.wikidata.org/wiki/Q176789","display_name":"Markov decision process","level":3,"score":0.41280001401901245},{"id":"https://openalex.org/C155512373","wikidata":"https://www.wikidata.org/wiki/Q287450","display_name":"Residual","level":2,"score":0.3944000005722046},{"id":"https://openalex.org/C168167062","wikidata":"https://www.wikidata.org/wiki/Q1117970","display_name":"Component (thermodynamics)","level":2,"score":0.39070001244544983},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.3833000063896179},{"id":"https://openalex.org/C159176650","wikidata":"https://www.wikidata.org/wiki/Q43261","display_name":"Horizon","level":2,"score":0.3711000084877014},{"id":"https://openalex.org/C107673813","wikidata":"https://www.wikidata.org/wiki/Q812534","display_name":"Bayesian probability","level":2,"score":0.35429999232292175},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.3522999882698059},{"id":"https://openalex.org/C2780813799","wikidata":"https://www.wikidata.org/wiki/Q3274237","display_name":"Zero (linguistics)","level":2,"score":0.33169999718666077},{"id":"https://openalex.org/C2776999362","wikidata":"https://www.wikidata.org/wiki/Q2349274","display_name":"Planner","level":2,"score":0.3292999863624573},{"id":"https://openalex.org/C2776502983","wikidata":"https://www.wikidata.org/wiki/Q690182","display_name":"Contrast (vision)","level":2,"score":0.31349998712539673},{"id":"https://openalex.org/C2775924081","wikidata":"https://www.wikidata.org/wiki/Q55608371","display_name":"Control (management)","level":2,"score":0.29899999499320984},{"id":"https://openalex.org/C177148314","wikidata":"https://www.wikidata.org/wiki/Q170084","display_name":"Generalization","level":2,"score":0.2948000133037567},{"id":"https://openalex.org/C106487976","wikidata":"https://www.wikidata.org/wiki/Q685816","display_name":"Matrix (chemical analysis)","level":2,"score":0.29280000925064087},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.29109999537467957},{"id":"https://openalex.org/C28761237","wikidata":"https://www.wikidata.org/wiki/Q7805321","display_name":"Time horizon","level":2,"score":0.288100004196167},{"id":"https://openalex.org/C2776937971","wikidata":"https://www.wikidata.org/wiki/Q4384217","display_name":"Heading (navigation)","level":2,"score":0.28110000491142273},{"id":"https://openalex.org/C144237770","wikidata":"https://www.wikidata.org/wiki/Q747534","display_name":"Mathematical economics","level":1,"score":0.2703999876976013},{"id":"https://openalex.org/C44154836","wikidata":"https://www.wikidata.org/wiki/Q45045","display_name":"Simulation","level":1,"score":0.263700008392334},{"id":"https://openalex.org/C141042865","wikidata":"https://www.wikidata.org/wiki/Q200125","display_name":"Expected value","level":2,"score":0.26350000500679016},{"id":"https://openalex.org/C22789450","wikidata":"https://www.wikidata.org/wiki/Q420904","display_name":"Singular value decomposition","level":2,"score":0.25369998812675476},{"id":"https://openalex.org/C42475967","wikidata":"https://www.wikidata.org/wiki/Q194292","display_name":"Operations research","level":1,"score":0.2502000033855438}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2605.21458","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.21458","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"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":null,"raw_source_name":null,"raw_type":"Preprint"}],"best_oa_location":{"id":"doi:10.48550/arxiv.2605.21458","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.21458","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"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"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/16","score":0.7130096554756165,"display_name":"Peace, Justice and strong institutions"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Suppose":[0],"a":[1,4,8,75,83,105,116,143,155,171,196,200,204],"planner":[2,53],"has":[3],"pre-trained":[5],"simulator":[6,23,57],"of":[7,154],"sequential":[9],"decision":[10],"problem":[11],"and":[12,31,50,82,100,115,161],"the":[13,20,52,56,70,93,97,101,110,150,168,181,188,211],"option":[14],"to":[15,26,186],"run":[16],"real":[17,43],"experiments":[18],"in":[19],"field.":[21],"The":[22,124],"is":[24,38,183],"cheap":[25],"query":[27],"but":[28,40],"inherits":[29],"confounding":[30],"drift":[32],"from":[33,130,203],"its":[34],"calibration":[35],"data.":[36],"Experimentation":[37],"unbiased":[39],"consumes":[41],"one":[42],"unit":[44],"per":[45],"trial.":[46],"We":[47,60],"study":[48],"when,":[49],"how,":[51],"should":[54],"supplement":[55],"with":[58,159,195],"experiments.":[59],"give":[61],"three":[62],"results.":[63],"First,":[64],"an":[65,191],"extended":[66],"simulation":[67],"lemma":[68],"decomposes":[69],"simulator's":[71],"value":[72,94],"error":[73],"into":[74,104],"calibration--deployment":[76],"shift":[77],"that":[78,86,148,198],"randomization":[79],"can":[80,90],"identify":[81],"parametric":[84],"residual":[85],"no":[87],"further":[88],"interaction":[89],"reduce.":[91],"Second,":[92],"gap":[95],"between":[96],"simulator-optimal":[98],"policy":[99,112,146],"optimum":[102],"splits":[103],"local":[106],"component,":[107,118],"on":[108,119],"states":[109,120],"deployed":[111],"already":[113],"visits,":[114],"reachability":[117,125],"it":[121],"does":[122],"not.":[123],"component":[126],"stays":[127],"bounded":[128],"away":[129],"zero":[131],"at":[132],"any":[133],"horizon":[134,182],"under":[135],"purely":[136],"passive":[137],"learning.":[138],"Third,":[139],"we":[140],"propose":[141],"Fisher-SEP,":[142],"simulation-aided":[144],"experimental":[145],"(SEP)":[147],"minimizes":[149],"posterior":[151,178],"predictive":[152],"variance":[153],"target":[156],"policy's":[157],"value,":[158],"reward-only":[160],"transition-only":[162],"specializations.":[163],"Two":[164],"case":[165],"studies":[166],"illustrate":[167],"regimes.":[169],"In":[170,190],"vending-machine":[172],"supply":[173],"chain,":[174],"front-loaded":[175],"experimentation":[176],"overtakes":[177],"updating":[179],"once":[180],"long":[184],"enough":[185],"amortize":[187],"pilot.":[189],"HIV":[192],"mobile-testing":[193],"example":[194],"corridor":[197],"separates":[199],"well-surveilled":[201],"region":[202],"poorly-surveilled":[205,212],"one,":[206],"only":[207],"designed":[208],"exploration":[209],"reaches":[210],"region.":[213]},"counts_by_year":[],"updated_date":"2026-07-01T06:00:48.157686","created_date":"2026-05-22T00:00:00"}