{"id":"https://openalex.org/W7136109428","doi":"https://doi.org/10.48550/arxiv.2603.12612","title":"FastDSAC: Unlocking the Potential of Maximum Entropy RL in High-Dimensional Humanoid Control","display_name":"FastDSAC: Unlocking the Potential of Maximum Entropy RL in High-Dimensional Humanoid Control","publication_year":2026,"publication_date":"2026-03-13","ids":{"openalex":"https://openalex.org/W7136109428","doi":"https://doi.org/10.48550/arxiv.2603.12612"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2603.12612","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.12612","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.2603.12612","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5101000170","display_name":"Jun Xue","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Xue, Jun","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5129452518","display_name":"Junze Wang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wang, Junze","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5113127926","display_name":"Shanze Wang","orcid":"https://orcid.org/0009-0001-4004-1056"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wang, Shanze","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5113127926","display_name":"Shanze Wang","orcid":"https://orcid.org/0009-0001-4004-1056"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhang, Xinming","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100410763","display_name":"Yanjun Chen","orcid":"https://orcid.org/0000-0003-0709-0208"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Chen, Yanjun","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5129399534","display_name":"Wei Emma Zhang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhang, Wei","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":0.46950000524520874,"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":0.46950000524520874,"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/T11689","display_name":"Adversarial Robustness in Machine Learning","score":0.10029999911785126,"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/T10653","display_name":"Robot Manipulation and Learning","score":0.06840000301599503,"subfield":{"id":"https://openalex.org/subfields/2207","display_name":"Control and Systems Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/reinforcement-learning","display_name":"Reinforcement learning","score":0.738099992275238},{"id":"https://openalex.org/keywords/inefficiency","display_name":"Inefficiency","score":0.5688999891281128},{"id":"https://openalex.org/keywords/principle-of-maximum-entropy","display_name":"Principle of maximum entropy","score":0.5174999833106995},{"id":"https://openalex.org/keywords/entropy","display_name":"Entropy (arrow of time)","score":0.4941999912261963},{"id":"https://openalex.org/keywords/optimal-control","display_name":"Optimal control","score":0.47040000557899475},{"id":"https://openalex.org/keywords/fidelity","display_name":"Fidelity","score":0.46399998664855957},{"id":"https://openalex.org/keywords/scaling","display_name":"Scaling","score":0.3856000006198883},{"id":"https://openalex.org/keywords/stochastic-control","display_name":"Stochastic control","score":0.34119999408721924}],"concepts":[{"id":"https://openalex.org/C97541855","wikidata":"https://www.wikidata.org/wiki/Q830687","display_name":"Reinforcement learning","level":2,"score":0.738099992275238},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6378999948501587},{"id":"https://openalex.org/C2778869765","wikidata":"https://www.wikidata.org/wiki/Q6028363","display_name":"Inefficiency","level":2,"score":0.5688999891281128},{"id":"https://openalex.org/C9679016","wikidata":"https://www.wikidata.org/wiki/Q1417473","display_name":"Principle of maximum entropy","level":2,"score":0.5174999833106995},{"id":"https://openalex.org/C106301342","wikidata":"https://www.wikidata.org/wiki/Q4117933","display_name":"Entropy (arrow of time)","level":2,"score":0.4941999912261963},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.47369998693466187},{"id":"https://openalex.org/C91575142","wikidata":"https://www.wikidata.org/wiki/Q1971426","display_name":"Optimal control","level":2,"score":0.47040000557899475},{"id":"https://openalex.org/C2776459999","wikidata":"https://www.wikidata.org/wiki/Q2119376","display_name":"Fidelity","level":2,"score":0.46399998664855957},{"id":"https://openalex.org/C99844830","wikidata":"https://www.wikidata.org/wiki/Q102441924","display_name":"Scaling","level":2,"score":0.3856000006198883},{"id":"https://openalex.org/C170131372","wikidata":"https://www.wikidata.org/wiki/Q7617811","display_name":"Stochastic control","level":3,"score":0.34119999408721924},{"id":"https://openalex.org/C47446073","wikidata":"https://www.wikidata.org/wiki/Q5165890","display_name":"Control theory (sociology)","level":3,"score":0.32409998774528503},{"id":"https://openalex.org/C106189395","wikidata":"https://www.wikidata.org/wiki/Q176789","display_name":"Markov decision process","level":3,"score":0.313400000333786},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.30469998717308044},{"id":"https://openalex.org/C113364801","wikidata":"https://www.wikidata.org/wiki/Q26674","display_name":"High fidelity","level":2,"score":0.2971999943256378},{"id":"https://openalex.org/C2780502288","wikidata":"https://www.wikidata.org/wiki/Q28838156","display_name":"Expansive","level":3,"score":0.29260000586509705},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.28290000557899475},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.2757999897003174},{"id":"https://openalex.org/C2775924081","wikidata":"https://www.wikidata.org/wiki/Q55608371","display_name":"Control (management)","level":2,"score":0.2750000059604645},{"id":"https://openalex.org/C188198153","wikidata":"https://www.wikidata.org/wiki/Q1613840","display_name":"Limiting","level":2,"score":0.2696000039577484},{"id":"https://openalex.org/C159886148","wikidata":"https://www.wikidata.org/wiki/Q176645","display_name":"Markov process","level":2,"score":0.2500999867916107}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2603.12612","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.12612","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.2603.12612","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.12612","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":{"Scaling":[0],"Maximum":[1],"Entropy":[2,61],"Reinforcement":[3],"Learning":[4],"(RL)":[5],"to":[6,64,76],"high-dimensional":[7,84,109],"humanoid":[8],"control":[9,100],"remains":[10],"a":[11,42,71,95],"fundamental":[12],"challenge,":[13],"as":[14],"the":[15,47,67,113,134],"''curse":[16],"of":[17,49,98,129],"dimensionality''":[18],"induces":[19],"severe":[20],"exploration":[21,68],"inefficiency":[22],"and":[23,86,94,121,131,137],"training":[24],"instability.":[25],"Consequently,":[26],"highly":[27],"optimized":[28],"deterministic":[29,125],"policy":[30],"gradients":[31],"currently":[32],"dominate":[33],"high-throughput":[34],"regimes.":[35],"We":[36,58],"address":[37],"this":[38],"limitation":[39],"with":[40,120,127],"FastDSAC,":[41],"framework":[43],"that":[44,103],"effectively":[45],"unlocks":[46],"potential":[48],"maximum":[50],"entropy":[51],"stochastic":[52,110],"policies":[53,111],"for":[54,108],"complex":[55],"continuous":[56,72,99],"control.":[57],"introduce":[59],"Dimension-wise":[60],"Modulation":[62],"(DEM)":[63],"dynamically":[65],"redistribute":[66],"budget,":[69],"alongside":[70],"distributional":[73],"critic":[74],"tailored":[75],"ensure":[77],"accurate":[78],"value":[79],"estimation":[80],"by":[81],"mitigating":[82],"both":[83],"overestimation":[85],"discrete":[87],"quantization":[88],"artifacts.":[89],"Extensive":[90],"evaluations":[91],"on":[92,112,133],"HumanoidBench":[93],"diverse":[96],"set":[97],"tasks":[101],"demonstrate":[102],"FastDSAC":[104],"establishes":[105],"state-of-the-art":[106],"performance":[107],"evaluated":[114],"benchmarks.":[115],"Our":[116],"method":[117],"is":[118],"competitive":[119],"often":[122],"outperforms":[123],"strong":[124],"baselines,":[126],"gains":[128],"180%":[130],"350%":[132],"challenging":[135],"Basketball":[136],"Balance":[138],"Hard":[139],"tasks,":[140],"respectively.":[141]},"counts_by_year":[],"updated_date":"2026-07-20T07:56:41.581041","created_date":"2026-03-17T00:00:00"}
