{"id":"https://openalex.org/W3091439543","doi":"https://doi.org/10.1109/ccta41146.2020.9206334","title":"Random-Sampling Multipath Hypothesis Propagation for Cost Approximation in Long-Horizon Optimal Control","display_name":"Random-Sampling Multipath Hypothesis Propagation for Cost Approximation in Long-Horizon Optimal Control","publication_year":2020,"publication_date":"2020-08-01","ids":{"openalex":"https://openalex.org/W3091439543","doi":"https://doi.org/10.1109/ccta41146.2020.9206334","mag":"3091439543"},"language":"en","primary_location":{"id":"doi:10.1109/ccta41146.2020.9206334","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ccta41146.2020.9206334","pdf_url":null,"source":{"id":"https://openalex.org/S4306498667","display_name":"2020 IEEE Conference on Control Technology and Applications (CCTA)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 IEEE Conference on Control Technology and Applications (CCTA)","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5052915033","display_name":"Shankarachary Ragi","orcid":"https://orcid.org/0000-0002-5511-4334"},"institutions":[{"id":"https://openalex.org/I184647316","display_name":"South Dakota School of Mines and Technology","ror":"https://ror.org/00ch7yk27","country_code":"US","type":"education","lineage":["https://openalex.org/I184647316"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Shankarachary Ragi","raw_affiliation_strings":["Department of Electrical Engineering, South Dakota School of Mines and Technology, Rapid City, SD, USA"],"affiliations":[{"raw_affiliation_string":"Department of Electrical Engineering, South Dakota School of Mines and Technology, Rapid City, SD, USA","institution_ids":["https://openalex.org/I184647316"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5048520206","display_name":"Hans D. Mittelmann","orcid":"https://orcid.org/0000-0003-1961-657X"},"institutions":[{"id":"https://openalex.org/I55732556","display_name":"Arizona State University","ror":"https://ror.org/03efmqc40","country_code":"US","type":"education","lineage":["https://openalex.org/I55732556"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Hans D. Mittelmann","raw_affiliation_strings":["School of Mathematical and Statistical Sciences, Arizona State University, Tempe, AZ, USA"],"affiliations":[{"raw_affiliation_string":"School of Mathematical and Statistical Sciences, Arizona State University, Tempe, AZ, USA","institution_ids":["https://openalex.org/I55732556"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5052915033"],"corresponding_institution_ids":["https://openalex.org/I184647316"],"apc_list":null,"apc_paid":null,"fwci":0.2206,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.52900964,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":94},"biblio":{"volume":"47","issue":null,"first_page":"14","last_page":"18"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12072","display_name":"Machine Learning and Algorithms","score":0.9988999962806702,"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/T12072","display_name":"Machine Learning and Algorithms","score":0.9988999962806702,"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/T12101","display_name":"Advanced Bandit Algorithms Research","score":0.9983000159263611,"subfield":{"id":"https://openalex.org/subfields/1803","display_name":"Management Science and Operations Research"},"field":{"id":"https://openalex.org/fields/18","display_name":"Decision Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T10791","display_name":"Advanced Control Systems Optimization","score":0.9975000023841858,"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/importance-sampling","display_name":"Importance sampling","score":0.601858913898468},{"id":"https://openalex.org/keywords/convergence","display_name":"Convergence (economics)","score":0.5934615731239319},{"id":"https://openalex.org/keywords/mathematical-optimization","display_name":"Mathematical optimization","score":0.5927241444587708},{"id":"https://openalex.org/keywords/sampling","display_name":"Sampling (signal processing)","score":0.5475994348526001},{"id":"https://openalex.org/keywords/heuristic","display_name":"Heuristic","score":0.5327686667442322},{"id":"https://openalex.org/keywords/monte-carlo-method","display_name":"Monte Carlo method","score":0.518721878528595},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.507293164730072},{"id":"https://openalex.org/keywords/stochastic-approximation","display_name":"Stochastic approximation","score":0.475448340177536},{"id":"https://openalex.org/keywords/optimal-control","display_name":"Optimal control","score":0.43744373321533203},{"id":"https://openalex.org/keywords/function-approximation","display_name":"Function approximation","score":0.4329186975955963},{"id":"https://openalex.org/keywords/approximation-theory","display_name":"Approximation theory","score":0.4257989823818207},{"id":"https://openalex.org/keywords/multipath-propagation","display_name":"Multipath propagation","score":0.4169501066207886},{"id":"https://openalex.org/keywords/linear-approximation","display_name":"Linear approximation","score":0.41105133295059204},{"id":"https://openalex.org/keywords/nonlinear-system","display_name":"Nonlinear system","score":0.39224955439567566},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.3627007007598877},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.11812663078308105},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.08640947937965393}],"concepts":[{"id":"https://openalex.org/C52740198","wikidata":"https://www.wikidata.org/wiki/Q1539564","display_name":"Importance sampling","level":3,"score":0.601858913898468},{"id":"https://openalex.org/C2777303404","wikidata":"https://www.wikidata.org/wiki/Q759757","display_name":"Convergence (economics)","level":2,"score":0.5934615731239319},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.5927241444587708},{"id":"https://openalex.org/C140779682","wikidata":"https://www.wikidata.org/wiki/Q210868","display_name":"Sampling (signal processing)","level":3,"score":0.5475994348526001},{"id":"https://openalex.org/C173801870","wikidata":"https://www.wikidata.org/wiki/Q201413","display_name":"Heuristic","level":2,"score":0.5327686667442322},{"id":"https://openalex.org/C19499675","wikidata":"https://www.wikidata.org/wiki/Q232207","display_name":"Monte Carlo method","level":2,"score":0.518721878528595},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.507293164730072},{"id":"https://openalex.org/C55479107","wikidata":"https://www.wikidata.org/wiki/Q97663916","display_name":"Stochastic approximation","level":3,"score":0.475448340177536},{"id":"https://openalex.org/C91575142","wikidata":"https://www.wikidata.org/wiki/Q1971426","display_name":"Optimal control","level":2,"score":0.43744373321533203},{"id":"https://openalex.org/C91873725","wikidata":"https://www.wikidata.org/wiki/Q3445816","display_name":"Function approximation","level":3,"score":0.4329186975955963},{"id":"https://openalex.org/C145242015","wikidata":"https://www.wikidata.org/wiki/Q774123","display_name":"Approximation theory","level":2,"score":0.4257989823818207},{"id":"https://openalex.org/C161218011","wikidata":"https://www.wikidata.org/wiki/Q11827794","display_name":"Multipath propagation","level":3,"score":0.4169501066207886},{"id":"https://openalex.org/C160824197","wikidata":"https://www.wikidata.org/wiki/Q2071054","display_name":"Linear approximation","level":3,"score":0.41105133295059204},{"id":"https://openalex.org/C158622935","wikidata":"https://www.wikidata.org/wiki/Q660848","display_name":"Nonlinear system","level":2,"score":0.39224955439567566},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.3627007007598877},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.11812663078308105},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.08640947937965393},{"id":"https://openalex.org/C127162648","wikidata":"https://www.wikidata.org/wiki/Q16858953","display_name":"Channel (broadcasting)","level":2,"score":0.0},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"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/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.0},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.0},{"id":"https://openalex.org/C50522688","wikidata":"https://www.wikidata.org/wiki/Q189833","display_name":"Economic growth","level":1,"score":0.0},{"id":"https://openalex.org/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","level":1,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.0},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/ccta41146.2020.9206334","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ccta41146.2020.9206334","pdf_url":null,"source":{"id":"https://openalex.org/S4306498667","display_name":"2020 IEEE Conference on Control Technology and Applications (CCTA)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 IEEE Conference on Control Technology and Applications (CCTA)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":11,"referenced_works":["https://openalex.org/W1995304567","https://openalex.org/W2000849559","https://openalex.org/W2089593831","https://openalex.org/W2113439731","https://openalex.org/W2126316555","https://openalex.org/W2140109495","https://openalex.org/W2147996349","https://openalex.org/W2164142425","https://openalex.org/W2735595527","https://openalex.org/W2963600139","https://openalex.org/W3016548437"],"related_works":["https://openalex.org/W2167394514","https://openalex.org/W2766569526","https://openalex.org/W2235525867","https://openalex.org/W1553308207","https://openalex.org/W2123358778","https://openalex.org/W1859974437","https://openalex.org/W4388667053","https://openalex.org/W2153714959","https://openalex.org/W2156766998","https://openalex.org/W3177870706"],"abstract_inverted_index":{"In":[0,21],"this":[1,22,91],"paper,":[2],"we":[3,24,126],"develop":[4],"a":[5,82,95,123,135],"Monte-Carlo":[6],"based":[7],"heuristic":[8],"approach":[9,146,154],"to":[10,94,129],"approximate":[11,130],"the":[12,26,33,37,45,49,53,73,76,103,108,118,131,142],"objective":[13],"function":[14,133],"in":[15,72,134],"long":[16],"horizon":[17],"optimal":[18],"control":[19,138],"problems.":[20],"approach,":[23],"evolve":[25],"system":[27],"state":[28],"over":[29],"multiple":[30],"trajectories":[31],"into":[32],"future":[34],"while":[35],"sampling":[36,60],"noise":[38],"disturbances":[39],"at":[40],"each":[41],"time-step,":[42],"and":[43,111,140,150],"find":[44],"weighted":[46],"average":[47],"of":[48,85,144],"costs":[50],"along":[51],"all":[52],"trajectories.":[54],"We":[55,98],"call":[56],"these":[57],"methods":[58,68,110],"random":[59],"-":[61],"multipath":[62],"hypothesis":[63],"propagation":[64],"or":[65],"RS-MHP.":[66],"These":[67],"(or":[69],"variants)":[70],"exist":[71],"literature;":[74],"however,":[75],"literature":[77],"lacks":[78],"convergence":[79,100,114],"results":[80,101],"for":[81,102],"generic":[83],"class":[84],"nonlinear":[86],"systems.":[87],"This":[88],"paper":[89],"fills":[90],"knowledge":[92],"gap":[93],"certain":[96],"extent.":[97],"derive":[99],"cost":[104,132],"approximation":[105,153],"error":[106],"from":[107],"MHP":[109],"discuss":[112],"their":[113],"(in":[115],"probability)":[116],"as":[117],"sample":[119],"size":[120],"increases.":[121],"As":[122],"case":[124],"study,":[125],"apply":[127],"RS-MHP":[128],"linear":[136],"quadratic":[137],"problem":[139],"demonstrate":[141],"benefits":[143],"our":[145],"against":[147],"an":[148],"existing":[149],"closely":[151],"related":[152],"called":[155],"nominal":[156],"belief-state":[157],"optimization.":[158]},"counts_by_year":[{"year":2022,"cited_by_count":1},{"year":2020,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
