{"id":"https://openalex.org/W4311991898","doi":"https://doi.org/10.48550/arxiv.2212.08235","title":"A Simple Decentralized Cross-Entropy Method","display_name":"A Simple Decentralized Cross-Entropy Method","publication_year":2022,"publication_date":"2022-12-16","ids":{"openalex":"https://openalex.org/W4311991898","doi":"https://doi.org/10.48550/arxiv.2212.08235"},"language":"en","primary_location":{"id":"pmh:oai:arXiv.org:2212.08235","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2212.08235","pdf_url":"https://arxiv.org/pdf/2212.08235","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":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"text"},"type":"preprint","indexed_in":["arxiv","datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2212.08235","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5100739122","display_name":"Zichen Zhang","orcid":"https://orcid.org/0009-0002-5836-7377"},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Zhang, Zichen","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5034582982","display_name":"Jun Jin","orcid":"https://orcid.org/0000-0001-9751-1293"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Jin, Jun","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5030948380","display_name":"Martin J\u00e4gersand","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Jagersand, Martin","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100391191","display_name":"Jun Luo","orcid":"https://orcid.org/0000-0002-1773-8023"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Luo, Jun","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5010575626","display_name":"Dale Schuurmans","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Schuurmans, Dale","raw_affiliation_strings":[],"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5100739122"],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":3,"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":0.9950000047683716,"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":0.9950000047683716,"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/T11663","display_name":"Viral Infectious Diseases and Gene Expression in Insects","score":0.9650999903678894,"subfield":{"id":"https://openalex.org/subfields/1312","display_name":"Molecular Biology"},"field":{"id":"https://openalex.org/fields/13","display_name":"Biochemistry, Genetics and Molecular Biology"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},{"id":"https://openalex.org/T11975","display_name":"Evolutionary Algorithms and Applications","score":0.9207000136375427,"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/computer-science","display_name":"Computer science","score":0.6889678835868835},{"id":"https://openalex.org/keywords/gaussian","display_name":"Gaussian","score":0.6220248937606812},{"id":"https://openalex.org/keywords/cross-entropy-method","display_name":"Cross-entropy method","score":0.5974968671798706},{"id":"https://openalex.org/keywords/reinforcement-learning","display_name":"Reinforcement learning","score":0.5663794875144958},{"id":"https://openalex.org/keywords/cross-entropy","display_name":"Cross entropy","score":0.529746413230896},{"id":"https://openalex.org/keywords/entropy","display_name":"Entropy (arrow of time)","score":0.5121886134147644},{"id":"https://openalex.org/keywords/local-optimum","display_name":"Local optimum","score":0.4954169988632202},{"id":"https://openalex.org/keywords/simple","display_name":"Simple (philosophy)","score":0.4675561189651489},{"id":"https://openalex.org/keywords/mathematical-optimization","display_name":"Mathematical optimization","score":0.45879456400871277},{"id":"https://openalex.org/keywords/sample","display_name":"Sample (material)","score":0.4498450458049774},{"id":"https://openalex.org/keywords/sampling","display_name":"Sampling (signal processing)","score":0.44178566336631775},{"id":"https://openalex.org/keywords/mixture-distribution","display_name":"Mixture distribution","score":0.43384256958961487},{"id":"https://openalex.org/keywords/principle-of-maximum-entropy","display_name":"Principle of maximum entropy","score":0.38284334540367126},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3291783630847931},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.2920657992362976},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.19270890951156616},{"id":"https://openalex.org/keywords/optimization-problem","display_name":"Optimization problem","score":0.1682802140712738},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.07975342869758606},{"id":"https://openalex.org/keywords/probability-density-function","display_name":"Probability density function","score":0.0701354444026947}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6889678835868835},{"id":"https://openalex.org/C163716315","wikidata":"https://www.wikidata.org/wiki/Q901177","display_name":"Gaussian","level":2,"score":0.6220248937606812},{"id":"https://openalex.org/C75782508","wikidata":"https://www.wikidata.org/wiki/Q3333633","display_name":"Cross-entropy method","level":4,"score":0.5974968671798706},{"id":"https://openalex.org/C97541855","wikidata":"https://www.wikidata.org/wiki/Q830687","display_name":"Reinforcement learning","level":2,"score":0.5663794875144958},{"id":"https://openalex.org/C167981619","wikidata":"https://www.wikidata.org/wiki/Q1685498","display_name":"Cross entropy","level":3,"score":0.529746413230896},{"id":"https://openalex.org/C106301342","wikidata":"https://www.wikidata.org/wiki/Q4117933","display_name":"Entropy (arrow of time)","level":2,"score":0.5121886134147644},{"id":"https://openalex.org/C141934464","wikidata":"https://www.wikidata.org/wiki/Q3305386","display_name":"Local optimum","level":2,"score":0.4954169988632202},{"id":"https://openalex.org/C2780586882","wikidata":"https://www.wikidata.org/wiki/Q7520643","display_name":"Simple (philosophy)","level":2,"score":0.4675561189651489},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.45879456400871277},{"id":"https://openalex.org/C198531522","wikidata":"https://www.wikidata.org/wiki/Q485146","display_name":"Sample (material)","level":2,"score":0.4498450458049774},{"id":"https://openalex.org/C140779682","wikidata":"https://www.wikidata.org/wiki/Q210868","display_name":"Sampling (signal processing)","level":3,"score":0.44178566336631775},{"id":"https://openalex.org/C56672385","wikidata":"https://www.wikidata.org/wiki/Q17157111","display_name":"Mixture distribution","level":3,"score":0.43384256958961487},{"id":"https://openalex.org/C9679016","wikidata":"https://www.wikidata.org/wiki/Q1417473","display_name":"Principle of maximum entropy","level":2,"score":0.38284334540367126},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3291783630847931},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.2920657992362976},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.19270890951156616},{"id":"https://openalex.org/C137836250","wikidata":"https://www.wikidata.org/wiki/Q984063","display_name":"Optimization problem","level":2,"score":0.1682802140712738},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.07975342869758606},{"id":"https://openalex.org/C197055811","wikidata":"https://www.wikidata.org/wiki/Q207522","display_name":"Probability density function","level":2,"score":0.0701354444026947},{"id":"https://openalex.org/C111472728","wikidata":"https://www.wikidata.org/wiki/Q9471","display_name":"Epistemology","level":1,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C43617362","wikidata":"https://www.wikidata.org/wiki/Q170050","display_name":"Chromatography","level":1,"score":0.0},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.0},{"id":"https://openalex.org/C98036226","wikidata":"https://www.wikidata.org/wiki/Q7268356","display_name":"Quadratic assignment problem","level":3,"score":0.0},{"id":"https://openalex.org/C106131492","wikidata":"https://www.wikidata.org/wiki/Q3072260","display_name":"Filter (signal processing)","level":2,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"pmh:oai:arXiv.org:2212.08235","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2212.08235","pdf_url":"https://arxiv.org/pdf/2212.08235","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":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"text"},{"id":"doi:10.48550/arxiv.2212.08235","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2212.08235","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":"pmh:oai:arXiv.org:2212.08235","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2212.08235","pdf_url":"https://arxiv.org/pdf/2212.08235","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":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"text"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":["https://openalex.org/W2080931671","https://openalex.org/W1584645679","https://openalex.org/W2400292122","https://openalex.org/W2770616710","https://openalex.org/W2052147111","https://openalex.org/W1980187201","https://openalex.org/W286550118","https://openalex.org/W1038253066","https://openalex.org/W2088933359","https://openalex.org/W3122506910"],"abstract_inverted_index":{"Cross-Entropy":[0],"Method":[1],"(CEM)":[2],"is":[3,17,214],"commonly":[4],"used":[5],"for":[6,209],"planning":[7,154],"in":[8,149,152,162],"model-based":[9],"reinforcement":[10],"learning":[11],"(MBRL)":[12],"where":[13],"a":[14,41,64,87,123,127,198],"centralized":[15,42,119],"approach":[16,43,120,161],"typically":[18],"utilized":[19],"to":[20,47,102,116,169],"update":[21],"the":[22,28,104,117,135,143,153,170,187],"sampling":[23,93],"distribution":[24],"based":[25,173],"on":[26,32],"only":[27,196],"top-$k$":[29],"operation's":[30],"results":[31],"samples.":[33],"In":[34],"this":[35,57,107],"paper,":[36],"we":[37,59,147,205],"show":[38,113,180],"that":[39],"such":[40],"makes":[44],"CEM":[45,62,77,172,189],"vulnerable":[46],"local":[48,88],"optima,":[49],"thus":[50,141],"impairing":[51],"its":[52,91],"sample":[53,144,181],"efficiency.":[54,145],"To":[55],"tackle":[56],"issue,":[58],"propose":[60],"Decentralized":[61],"(DecentCEM),":[63],"simple":[65,108],"but":[66],"effective":[67],"improvement":[68,89,183],"over":[69],"classical":[70,118,188],"CEM,":[71],"by":[72,184],"using":[73,121],"an":[74],"ensemble":[75],"of":[76,90,106,129,156,201],"instances":[78],"running":[79],"independently":[80],"from":[81],"one":[82],"another,":[83],"and":[84,99,158,177],"each":[85],"performing":[86],"own":[92],"distribution.":[94],"We":[95,111],"provide":[96],"both":[97],"theoretical":[98],"empirical":[100],"analysis":[101],"demonstrate":[103],"effectiveness":[105],"decentralized":[109],"approach.":[110],"empirically":[112],"that,":[114],"compared":[115],"either":[122],"single":[124],"or":[125],"even":[126],"mixture":[128],"Gaussian":[130],"distributions,":[131],"our":[132,150,160,192],"DecentCEM":[133,151,193],"finds":[134],"global":[136],"optimum":[137],"much":[138],"more":[139,210],"consistently":[140],"improves":[142],"Furthermore,":[146],"plug":[148],"problem":[155],"MBRL,":[157],"evaluate":[159],"several":[163],"continuous":[164],"control":[165],"environments,":[166],"with":[167,191],"comparison":[168],"state-of-art":[171],"MBRL":[174],"approaches":[175],"(PETS":[176],"POPLIN).":[178],"Results":[179],"efficiency":[182],"simply":[185],"replacing":[186],"module":[190],"module,":[194],"while":[195],"sacrificing":[197],"reasonable":[199],"amount":[200],"computational":[202],"cost.":[203],"Lastly,":[204],"conduct":[206],"ablation":[207],"studies":[208],"in-depth":[211],"analysis.":[212],"Code":[213],"available":[215],"at":[216],"https://github.com/vincentzhang/decentCEM":[217]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":2}],"updated_date":"2026-02-09T09:26:11.010843","created_date":"2025-10-10T00:00:00"}