{"id":"https://openalex.org/W7160979478","doi":"https://doi.org/10.48550/arxiv.2605.11711","title":"Debiased Model-based Representations for Sample-efficient Continuous Control","display_name":"Debiased Model-based Representations for Sample-efficient Continuous Control","publication_year":2026,"publication_date":"2026-05-12","ids":{"openalex":"https://openalex.org/W7160979478","doi":"https://doi.org/10.48550/arxiv.2605.11711"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2605.11711","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.11711","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":"article"},"type":"preprint","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.48550/arxiv.2605.11711","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5136005333","display_name":"Jiafei Lyu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Lyu, Jiafei","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5136055367","display_name":"Zichuan Lin","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Lin, Zichuan","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5136014722","display_name":"Scott Fujimoto","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Fujimoto, Scott","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5136043025","display_name":"Kai Yang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yang, Kai","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5004408878","display_name":"Yangkun Chen","orcid":"https://orcid.org/0000-0001-8274-3921"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Chen, Yangkun","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5027918344","display_name":"Saiyong Yang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yang, Saiyong","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5136072717","display_name":"Zongqing Lu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Lu, Zongqing","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5136002621","display_name":"Deheng Ye","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Ye, Deheng","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":8,"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":0.590399980545044,"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":0.590399980545044,"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":0.11760000139474869,"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/T11206","display_name":"Model Reduction and Neural Networks","score":0.052799999713897705,"subfield":{"id":"https://openalex.org/subfields/3109","display_name":"Statistical and Nonlinear Physics"},"field":{"id":"https://openalex.org/fields/31","display_name":"Physics and Astronomy"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/overfitting","display_name":"Overfitting","score":0.8138999938964844},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.6708999872207642},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.6007999777793884},{"id":"https://openalex.org/keywords/control","display_name":"Control (management)","score":0.4878999888896942},{"id":"https://openalex.org/keywords/code","display_name":"Code (set theory)","score":0.4388999938964844},{"id":"https://openalex.org/keywords/mutual-information","display_name":"Mutual information","score":0.42989999055862427},{"id":"https://openalex.org/keywords/state","display_name":"State (computer science)","score":0.35910001397132874}],"concepts":[{"id":"https://openalex.org/C22019652","wikidata":"https://www.wikidata.org/wiki/Q331309","display_name":"Overfitting","level":3,"score":0.8138999938964844},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7336000204086304},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.6708999872207642},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.6007999777793884},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5044999718666077},{"id":"https://openalex.org/C2775924081","wikidata":"https://www.wikidata.org/wiki/Q55608371","display_name":"Control (management)","level":2,"score":0.4878999888896942},{"id":"https://openalex.org/C2776760102","wikidata":"https://www.wikidata.org/wiki/Q5139990","display_name":"Code (set theory)","level":3,"score":0.4388999938964844},{"id":"https://openalex.org/C152139883","wikidata":"https://www.wikidata.org/wiki/Q252973","display_name":"Mutual information","level":2,"score":0.42989999055862427},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.39579999446868896},{"id":"https://openalex.org/C48103436","wikidata":"https://www.wikidata.org/wiki/Q599031","display_name":"State (computer science)","level":2,"score":0.35910001397132874},{"id":"https://openalex.org/C177148314","wikidata":"https://www.wikidata.org/wiki/Q170084","display_name":"Generalization","level":2,"score":0.34779998660087585},{"id":"https://openalex.org/C43126263","wikidata":"https://www.wikidata.org/wiki/Q128751","display_name":"Source code","level":2,"score":0.3125},{"id":"https://openalex.org/C7797323","wikidata":"https://www.wikidata.org/wiki/Q3798612","display_name":"Pointwise mutual information","level":3,"score":0.28540000319480896},{"id":"https://openalex.org/C2778112365","wikidata":"https://www.wikidata.org/wiki/Q3511065","display_name":"Sequence (biology)","level":2,"score":0.2648000121116638},{"id":"https://openalex.org/C113336015","wikidata":"https://www.wikidata.org/wiki/Q574010","display_name":"Complete information","level":2,"score":0.26339998841285706},{"id":"https://openalex.org/C59404180","wikidata":"https://www.wikidata.org/wiki/Q17013334","display_name":"Feature learning","level":2,"score":0.26100000739097595},{"id":"https://openalex.org/C51632099","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Training set","level":2,"score":0.2506999969482422}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2605.11711","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.11711","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":"article"}],"best_oa_location":{"id":"doi:10.48550/arxiv.2605.11711","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.11711","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":"article"},"sustainable_development_goals":[{"score":0.7062376737594604,"display_name":"Peace, Justice and strong institutions","id":"https://metadata.un.org/sdg/16"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Model-based":[0],"representations":[1,16,99],"recently":[2],"stand":[3],"out":[4],"as":[5],"a":[6,130,152],"promising":[7],"framework":[8],"that":[9,139],"embeds":[10],"latent":[11],"dynamics":[12],"information":[13,52,96],"into":[14],"the":[15,25,35,63,94,98,101,106,136],"for":[17,86],"downstream":[18],"off-policy":[19],"actor-critic":[20,72],"learning.":[21],"It":[22],"implicitly":[23],"combines":[24],"advantages":[26],"of":[27,100,133],"both":[28],"model-free":[29],"and":[30,56,71,105,113,135],"model-based":[31,40,44,84],"approaches":[32],"while":[33],"avoiding":[34],"training":[36],"costs":[37],"associated":[38],"with":[39,116,129],"methods.":[41],"Nevertheless,":[42],"existing":[43],"representation":[45,70],"methods":[46],"can":[47,57,141],"fail":[48],"to":[49,59,75],"capture":[50],"sufficient":[51],"about":[53],"relevant":[54],"variables":[55],"overfit":[58],"early":[60],"experiences":[61],"in":[62,69],"replay":[64],"buffer.":[65],"These":[66],"incur":[67],"biases":[68],"learning,":[73],"leading":[74],"inferior":[76],"performance.":[77],"To":[78],"address":[79],"this,":[80],"we":[81],"propose":[82],"Debiased":[83],"Representations":[85],"Q-learning,":[87],"tagged":[88],"DR.Q":[89,91,123,140],"algorithm.":[90],"explicitly":[92],"maximizes":[93],"mutual":[95],"between":[97],"current":[102],"state-action":[103],"pair":[104],"next":[107],"state":[108],"besides":[109],"minimizing":[110],"their":[111],"deviations,":[112],"samples":[114],"transitions":[115],"faded":[117],"prioritized":[118],"experience":[119],"replay.":[120],"We":[121],"evaluate":[122],"on":[124],"numerous":[125],"continuous":[126],"control":[127],"benchmarks":[128],"single":[131],"set":[132],"hyperparameters,":[134],"results":[137],"demonstrate":[138],"match":[142],"or":[143],"surpass":[144],"recent":[145],"strong":[146],"baselines,":[147],"sometimes":[148],"outperforming":[149],"them":[150],"by":[151],"large":[153],"margin.":[154],"Our":[155],"code":[156],"is":[157],"available":[158],"at":[159],"https://github.com/dmksjfl/DR.Q.":[160]},"counts_by_year":[],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2026-05-14T00:00:00"}