{"id":"https://openalex.org/W7154255059","doi":"https://doi.org/10.48550/arxiv.2604.11463","title":"To Learn or Not to Learn: A Litmus Test for Using Reinforcement Learning in Control","display_name":"To Learn or Not to Learn: A Litmus Test for Using Reinforcement Learning in Control","publication_year":2026,"publication_date":"2026-04-13","ids":{"openalex":"https://openalex.org/W7154255059","doi":"https://doi.org/10.48550/arxiv.2604.11463"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2604.11463","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.11463","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":null,"license_id":null,"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.2604.11463","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5004608440","display_name":"Victor Schulte","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Schulte, Victor","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5129707311","display_name":"Michael Eichelbeck","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Eichelbeck, Michael","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5118214090","display_name":"Matthias Althoff","orcid":"https://orcid.org/0000-0002-6905-3456"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Althoff, Matthias","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/T10462","display_name":"Reinforcement Learning in Robotics","score":0.863099992275238,"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":0.863099992275238,"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/T12794","display_name":"Adaptive Dynamic Programming Control","score":0.02290000021457672,"subfield":{"id":"https://openalex.org/subfields/1703","display_name":"Computational Theory and Mathematics"},"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/T11689","display_name":"Adversarial Robustness in Machine Learning","score":0.01679999940097332,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/litmus","display_name":"Litmus","score":0.7932000160217285},{"id":"https://openalex.org/keywords/reinforcement-learning","display_name":"Reinforcement learning","score":0.7059999704360962},{"id":"https://openalex.org/keywords/control","display_name":"Control (management)","score":0.6797000169754028},{"id":"https://openalex.org/keywords/learnability","display_name":"Learnability","score":0.520799994468689},{"id":"https://openalex.org/keywords/test","display_name":"Test (biology)","score":0.3776000142097473},{"id":"https://openalex.org/keywords/optimal-control","display_name":"Optimal control","score":0.36480000615119934}],"concepts":[{"id":"https://openalex.org/C157329479","wikidata":"https://www.wikidata.org/wiki/Q185082","display_name":"Litmus","level":2,"score":0.7932000160217285},{"id":"https://openalex.org/C97541855","wikidata":"https://www.wikidata.org/wiki/Q830687","display_name":"Reinforcement learning","level":2,"score":0.7059999704360962},{"id":"https://openalex.org/C2775924081","wikidata":"https://www.wikidata.org/wiki/Q55608371","display_name":"Control (management)","level":2,"score":0.6797000169754028},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5616000294685364},{"id":"https://openalex.org/C2777723229","wikidata":"https://www.wikidata.org/wiki/Q4367921","display_name":"Learnability","level":2,"score":0.520799994468689},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.45820000767707825},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.44269999861717224},{"id":"https://openalex.org/C2777267654","wikidata":"https://www.wikidata.org/wiki/Q3519023","display_name":"Test (biology)","level":2,"score":0.3776000142097473},{"id":"https://openalex.org/C91575142","wikidata":"https://www.wikidata.org/wiki/Q1971426","display_name":"Optimal control","level":2,"score":0.36480000615119934},{"id":"https://openalex.org/C204323151","wikidata":"https://www.wikidata.org/wiki/Q905424","display_name":"Range (aeronautics)","level":2,"score":0.34299999475479126},{"id":"https://openalex.org/C116834253","wikidata":"https://www.wikidata.org/wiki/Q2039217","display_name":"Identification (biology)","level":2,"score":0.336899995803833},{"id":"https://openalex.org/C17500928","wikidata":"https://www.wikidata.org/wiki/Q959968","display_name":"Control system","level":2,"score":0.2865000069141388},{"id":"https://openalex.org/C67203356","wikidata":"https://www.wikidata.org/wiki/Q1321905","display_name":"Reinforcement","level":2,"score":0.2702000141143799},{"id":"https://openalex.org/C148220186","wikidata":"https://www.wikidata.org/wiki/Q7111912","display_name":"Outcome (game theory)","level":2,"score":0.265500009059906},{"id":"https://openalex.org/C25343380","wikidata":"https://www.wikidata.org/wiki/Q277521","display_name":"Relation (database)","level":2,"score":0.25119999051094055}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2604.11463","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.11463","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":null,"license_id":null,"version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"Preprint"}],"best_oa_location":{"id":"doi:10.48550/arxiv.2604.11463","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.11463","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":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Preprint"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Reinforcement":[0],"learning":[1],"(RL)":[2],"can":[3],"be":[4,55],"a":[5,21,99,153,176,195],"powerful":[6],"alternative":[7],"to":[8,43,57,63,68,81,112,188,194,205],"classical":[9],"control":[10,15,38,53,87,109,126,136,177,199],"methods":[11],"when":[12,19],"standard":[13],"model-based":[14,35,69,113,125],"is":[16,24,39,61,110,150],"insufficient,":[17],"e.g.,":[18],"deriving":[20],"suitable":[22],"model":[23,123,132,143],"intractable":[25],"or":[26],"impossible.":[27],"In":[28,94],"many":[29],"cases,":[30],"however,":[31],"the":[32,44,72,83,118,121,129,135,157,171,203],"choice":[33],"between":[34],"and":[36,201],"RL-based":[37,52,86,108],"not":[40,90],"obvious.":[41],"Due":[42],"high":[45],"computational":[46,207],"costs":[47],"of":[48,74,85,120,131,156,173,198],"training":[49,180],"RL":[50,92,174,182],"agents,":[51],"should":[54],"limited":[56],"cases":[58],"where":[59],"it":[60],"expected":[62],"yield":[64],"superior":[65,111],"results":[66],"compared":[67],"control.":[70,114],"To":[71],"best":[73],"our":[75,186],"knowledge,":[76],"there":[77],"exists":[78],"no":[79],"approach":[80],"quantify":[82],"benefit":[84],"that":[88],"does":[89],"require":[91],"training.":[93],"this":[95],"work,":[96],"we":[97,140],"present":[98],"computationally":[100],"efficient,":[101],"purely":[102],"simulation-based":[103,147],"litmus":[104],"test":[105,116,187],"predicting":[106],"whether":[107],"Our":[115],"evaluates":[117],"suitability":[119,172],"given":[122],"for":[124,175],"by":[127,152],"analyzing":[128],"impact":[130],"uncertainties":[133,158],"on":[134,160,170],"problem.":[137],"For":[138],"this,":[139],"use":[141],"reachset-conformant":[142],"identification":[144],"combined":[145],"with":[146],"analysis.":[148,162],"This":[149,163],"followed":[151],"learnability":[154],"evaluation":[155],"based":[159],"correlation":[161],"two-part":[164],"analysis":[165],"enables":[166],"an":[167,181],"informed":[168],"decision":[169],"problem":[178],"without":[179],"agent.":[183],"We":[184],"apply":[185],"several":[189],"benchmarks,":[190],"demonstrating":[191],"its":[192],"applicability":[193],"wide":[196],"range":[197],"problems":[200],"highlight":[202],"potential":[204],"save":[206],"resources.":[208]},"counts_by_year":[],"updated_date":"2026-07-01T06:00:48.157686","created_date":"2026-04-15T00:00:00"}