{"id":"https://openalex.org/W7160495016","doi":"https://doi.org/10.48550/arxiv.2605.04555","title":"Counter-Dyna: Data-Efficient RL-Based HVAC Control using Counterfactual Building Models","display_name":"Counter-Dyna: Data-Efficient RL-Based HVAC Control using Counterfactual Building Models","publication_year":2026,"publication_date":"2026-05-06","ids":{"openalex":"https://openalex.org/W7160495016","doi":"https://doi.org/10.48550/arxiv.2605.04555"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2605.04555","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.04555","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,"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.2605.04555","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5113187249","display_name":"Jan Marco Ruiz de Vargas","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"de Vargas, Jan Marco Ruiz","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5116019670","display_name":"Fabian Raisch","orcid":"https://orcid.org/0000-0003-1869-9801"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Raisch, Fabian","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5135617151","display_name":"Zoltan Nagy","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Nagy, Zoltan","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5058698672","display_name":"Pierre Pinson","orcid":"https://orcid.org/0000-0002-1480-0282"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Pinson, Pierre","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5054552711","display_name":"C Goebel","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Goebel, Christoph","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/T10121","display_name":"Building Energy and Comfort Optimization","score":0.45329999923706055,"subfield":{"id":"https://openalex.org/subfields/2215","display_name":"Building and Construction"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T10121","display_name":"Building Energy and Comfort Optimization","score":0.45329999923706055,"subfield":{"id":"https://openalex.org/subfields/2215","display_name":"Building and Construction"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10603","display_name":"Smart Grid Energy Management","score":0.3862999975681305,"subfield":{"id":"https://openalex.org/subfields/2208","display_name":"Electrical and Electronic Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10462","display_name":"Reinforcement Learning in Robotics","score":0.025499999523162842,"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/counterfactual-thinking","display_name":"Counterfactual thinking","score":0.7630000114440918},{"id":"https://openalex.org/keywords/reinforcement-learning","display_name":"Reinforcement learning","score":0.6876999735832214},{"id":"https://openalex.org/keywords/hvac","display_name":"HVAC","score":0.6414999961853027},{"id":"https://openalex.org/keywords/software-deployment","display_name":"Software deployment","score":0.574400007724762},{"id":"https://openalex.org/keywords/control","display_name":"Control (management)","score":0.5245000123977661},{"id":"https://openalex.org/keywords/key","display_name":"Key (lock)","score":0.4059999883174896},{"id":"https://openalex.org/keywords/model-predictive-control","display_name":"Model predictive control","score":0.39250001311302185},{"id":"https://openalex.org/keywords/energy","display_name":"Energy (signal processing)","score":0.3896999955177307}],"concepts":[{"id":"https://openalex.org/C108650721","wikidata":"https://www.wikidata.org/wiki/Q1783253","display_name":"Counterfactual thinking","level":2,"score":0.7630000114440918},{"id":"https://openalex.org/C97541855","wikidata":"https://www.wikidata.org/wiki/Q830687","display_name":"Reinforcement learning","level":2,"score":0.6876999735832214},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6794999837875366},{"id":"https://openalex.org/C122346748","wikidata":"https://www.wikidata.org/wiki/Q1798773","display_name":"HVAC","level":3,"score":0.6414999961853027},{"id":"https://openalex.org/C105339364","wikidata":"https://www.wikidata.org/wiki/Q2297740","display_name":"Software deployment","level":2,"score":0.574400007724762},{"id":"https://openalex.org/C2775924081","wikidata":"https://www.wikidata.org/wiki/Q55608371","display_name":"Control (management)","level":2,"score":0.5245000123977661},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.4059999883174896},{"id":"https://openalex.org/C172205157","wikidata":"https://www.wikidata.org/wiki/Q1782962","display_name":"Model predictive control","level":3,"score":0.39250001311302185},{"id":"https://openalex.org/C186370098","wikidata":"https://www.wikidata.org/wiki/Q442787","display_name":"Energy (signal processing)","level":2,"score":0.3896999955177307},{"id":"https://openalex.org/C206658404","wikidata":"https://www.wikidata.org/wiki/Q12725","display_name":"Electricity","level":2,"score":0.38679999113082886},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.38029998540878296},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.37070000171661377},{"id":"https://openalex.org/C18762648","wikidata":"https://www.wikidata.org/wiki/Q42213","display_name":"Work (physics)","level":2,"score":0.3488999903202057},{"id":"https://openalex.org/C133731056","wikidata":"https://www.wikidata.org/wiki/Q4917288","display_name":"Control engineering","level":1,"score":0.32269999384880066},{"id":"https://openalex.org/C2777211547","wikidata":"https://www.wikidata.org/wiki/Q17141490","display_name":"Training (meteorology)","level":2,"score":0.31060001254081726},{"id":"https://openalex.org/C7817414","wikidata":"https://www.wikidata.org/wiki/Q1779504","display_name":"Energy management","level":3,"score":0.2766999900341034},{"id":"https://openalex.org/C2780440489","wikidata":"https://www.wikidata.org/wiki/Q5227278","display_name":"Data-driven","level":2,"score":0.27379998564720154},{"id":"https://openalex.org/C2777303404","wikidata":"https://www.wikidata.org/wiki/Q759757","display_name":"Convergence (economics)","level":2,"score":0.2696000039577484},{"id":"https://openalex.org/C43214815","wikidata":"https://www.wikidata.org/wiki/Q7310987","display_name":"Reliability (semiconductor)","level":3,"score":0.263700008392334},{"id":"https://openalex.org/C17500928","wikidata":"https://www.wikidata.org/wiki/Q959968","display_name":"Control system","level":2,"score":0.2538999915122986},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.2513999938964844},{"id":"https://openalex.org/C2742236","wikidata":"https://www.wikidata.org/wiki/Q924713","display_name":"Efficient energy use","level":2,"score":0.25040000677108765}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2605.04555","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.04555","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,"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.2605.04555","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.04555","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,"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":[{"id":"https://metadata.un.org/sdg/7","score":0.8945642709732056,"display_name":"Affordable and clean energy"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Model-based":[0],"reinforcement":[1,21],"learning":[2],"(MBRL)":[3],"offers":[4],"a":[5,48,88,113,153,182,189],"promising":[6],"approach":[7],"for":[8],"data-efficient":[9,101],"energy":[10],"management":[11],"in":[12,109,115,122,152,181,199],"buildings,":[13],"combining":[14],"the":[15,44,63,92,110,158,169],"strengths":[16],"of":[17,41,94,139,177,196],"predictive":[18],"modeling":[19],"and":[20,68,163],"learning.":[22],"While":[23],"previous":[24,128,133],"MBRL":[25,97],"methods":[26],"applied":[27],"to":[28,46,61,127,179],"HVAC":[29,200],"control":[30,50,75,201],"have":[31],"reduced":[32],"training":[33,120],"data":[34,125],"requirements,":[35],"they":[36],"still":[37],"require":[38],"several":[39],"months":[40,138],"interaction":[42,124],"with":[43,132],"building":[45],"learn":[47],"satisfactory":[49],"policy.":[51],"A":[52],"key":[53],"reason":[54],"is":[55,188],"that":[56,71,90,135],"existing":[57],"surrogate":[58,103],"models":[59,104],"attempt":[60],"predict":[62],"entire":[64],"state-space,":[65],"including":[66],"weather":[67],"electricity":[69],"prices":[70],"are":[72],"unaffected":[73],"by":[74,106],"actions,":[76],"or":[77],"completely":[78],"ignore":[79],"these":[80,83],"variables.":[81],"Addressing":[82],"issues,":[84],"we":[85],"propose":[86],"Counter-Dyna,":[87],"method":[89,143,151],"enhances":[91],"data-efficiency":[93],"Dyna,":[95],"an":[96],"method.":[98],"We":[99,148],"create":[100],"counterfactual":[102],"(CSM)":[105],"leveraging":[107],"invariances":[108],"state-space.":[111],"Using":[112],"CSM":[114],"Dyna":[116],"speeds":[117],"up":[118],"RL":[119,170,197],"measured":[121],"environment":[123,140],"compared":[126],"results.":[129],"In":[130],"comparison":[131],"state-of-the-art":[134],"used":[136],"6-12":[137],"interactions,":[141],"our":[142,150],"needs":[144],"only":[145],"5":[146],"weeks.":[147],"evaluate":[149],"large":[154],"simulation":[155],"study":[156],"using":[157],"literature":[159],"standard":[160],"BOPTEST":[161],"framework":[162],"proximal":[164],"policy":[165],"algorithm":[166],"(PPO)":[167],"as":[168],"algorithm.":[171],"Our":[172,186],"results":[173],"show":[174],"cost-saving":[175],"potentials":[176],"5.3%":[178],"17.0%":[180],"hypothetical":[183],"deployment":[184,195],"scenario.":[185],"work":[187],"significant":[190],"step":[191],"towards":[192],"making":[193],"real-world":[194],"algorithms":[198],"practically":[202],"viable.":[203]},"counts_by_year":[],"updated_date":"2026-07-28T07:46:37.118299","created_date":"2026-05-08T00:00:00"}