{"id":"https://openalex.org/W2885769506","doi":"https://doi.org/10.1007/s10489-018-1248-5","title":"Posterior sampling for Monte Carlo planning under uncertainty","display_name":"Posterior sampling for Monte Carlo planning under uncertainty","publication_year":2018,"publication_date":"2018-08-15","ids":{"openalex":"https://openalex.org/W2885769506","doi":"https://doi.org/10.1007/s10489-018-1248-5","mag":"2885769506"},"language":"en","primary_location":{"id":"doi:10.1007/s10489-018-1248-5","is_oa":false,"landing_page_url":"https://doi.org/10.1007/s10489-018-1248-5","pdf_url":null,"source":{"id":"https://openalex.org/S74726891","display_name":"Applied Intelligence","issn_l":"0924-669X","issn":["0924-669X","1573-7497"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Applied Intelligence","raw_type":"journal-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/A5083303426","display_name":"Aijun Bai","orcid":"https://orcid.org/0000-0002-5164-4629"},"institutions":[{"id":"https://openalex.org/I1290206253","display_name":"Microsoft (United States)","ror":"https://ror.org/00d0nc645","country_code":"US","type":"company","lineage":["https://openalex.org/I1290206253"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Aijun Bai","raw_affiliation_strings":["Cloud & AI One Microsoft Way, Redmond, WA, 98052, USA","Cloud & AI One Microsoft Way, Redmond, USA"],"raw_orcid":"https://orcid.org/0000-0002-5164-4629","affiliations":[{"raw_affiliation_string":"Cloud & AI One Microsoft Way, Redmond, WA, 98052, USA","institution_ids":["https://openalex.org/I1290206253"]},{"raw_affiliation_string":"Cloud & AI One Microsoft Way, Redmond, USA","institution_ids":["https://openalex.org/I1290206253"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5029102289","display_name":"Feng Wu","orcid":"https://orcid.org/0000-0003-3989-0509"},"institutions":[{"id":"https://openalex.org/I126520041","display_name":"University of Science and Technology of China","ror":"https://ror.org/04c4dkn09","country_code":"CN","type":"education","lineage":["https://openalex.org/I126520041","https://openalex.org/I19820366"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Feng Wu","raw_affiliation_strings":["University of Science and Technology of China, 96 Jinzhai Road, Hefei, Anhui, 230026, China","University of Science and Technology of China, Hefei, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Science and Technology of China, 96 Jinzhai Road, Hefei, Anhui, 230026, China","institution_ids":["https://openalex.org/I126520041"]},{"raw_affiliation_string":"University of Science and Technology of China, Hefei, China","institution_ids":["https://openalex.org/I126520041"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5084710341","display_name":"Xiaoping Chen","orcid":"https://orcid.org/0000-0001-8992-9286"},"institutions":[{"id":"https://openalex.org/I126520041","display_name":"University of Science and Technology of China","ror":"https://ror.org/04c4dkn09","country_code":"CN","type":"education","lineage":["https://openalex.org/I126520041","https://openalex.org/I19820366"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiaoping Chen","raw_affiliation_strings":["University of Science and Technology of China, 96 Jinzhai Road, Hefei, Anhui, 230026, China","University of Science and Technology of China, Hefei, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Science and Technology of China, 96 Jinzhai Road, Hefei, Anhui, 230026, China","institution_ids":["https://openalex.org/I126520041"]},{"raw_affiliation_string":"University of Science and Technology of China, Hefei, China","institution_ids":["https://openalex.org/I126520041"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5029102289"],"corresponding_institution_ids":["https://openalex.org/I126520041"],"apc_list":{"value":2390,"currency":"EUR","value_usd":2990},"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":7,"citation_normalized_percentile":{"value":0.08384557,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":98},"biblio":{"volume":"48","issue":"12","first_page":"4998","last_page":"5018"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10462","display_name":"Reinforcement Learning in Robotics","score":0.9993000030517578,"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":0.9993000030517578,"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/T12072","display_name":"Machine Learning and Algorithms","score":0.9980999827384949,"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/T11574","display_name":"Artificial Intelligence in Games","score":0.988099992275238,"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":0.7737817764282227},{"id":"https://openalex.org/keywords/thompson-sampling","display_name":"Thompson sampling","score":0.6180105209350586},{"id":"https://openalex.org/keywords/partially-observable-markov-decision-process","display_name":"Partially observable Markov decision process","score":0.5693167448043823},{"id":"https://openalex.org/keywords/markov-chain-monte-carlo","display_name":"Markov chain Monte Carlo","score":0.5529360175132751},{"id":"https://openalex.org/keywords/dirichlet-process","display_name":"Dirichlet process","score":0.5416927337646484},{"id":"https://openalex.org/keywords/monte-carlo-tree-search","display_name":"Monte Carlo tree search","score":0.5293170809745789},{"id":"https://openalex.org/keywords/posterior-probability","display_name":"Posterior probability","score":0.5130351781845093},{"id":"https://openalex.org/keywords/monte-carlo-method","display_name":"Monte Carlo method","score":0.48849308490753174},{"id":"https://openalex.org/keywords/dirichlet-distribution","display_name":"Dirichlet distribution","score":0.48630866408348083},{"id":"https://openalex.org/keywords/tree","display_name":"Tree (set theory)","score":0.4382099211215973},{"id":"https://openalex.org/keywords/mathematical-optimization","display_name":"Mathematical optimization","score":0.42457765340805054},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3908610939979553},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3371732831001282},{"id":"https://openalex.org/keywords/bayesian-probability","display_name":"Bayesian probability","score":0.33237600326538086},{"id":"https://openalex.org/keywords/markov-model","display_name":"Markov model","score":0.1960829496383667},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.18971103429794312},{"id":"https://openalex.org/keywords/markov-chain","display_name":"Markov chain","score":0.18177738785743713},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.10560441017150879}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7737817764282227},{"id":"https://openalex.org/C73602740","wikidata":"https://www.wikidata.org/wiki/Q7795822","display_name":"Thompson sampling","level":3,"score":0.6180105209350586},{"id":"https://openalex.org/C17098449","wikidata":"https://www.wikidata.org/wiki/Q176814","display_name":"Partially observable Markov decision process","level":4,"score":0.5693167448043823},{"id":"https://openalex.org/C111350023","wikidata":"https://www.wikidata.org/wiki/Q1191869","display_name":"Markov chain Monte Carlo","level":3,"score":0.5529360175132751},{"id":"https://openalex.org/C2781280628","wikidata":"https://www.wikidata.org/wiki/Q5280766","display_name":"Dirichlet process","level":3,"score":0.5416927337646484},{"id":"https://openalex.org/C46149586","wikidata":"https://www.wikidata.org/wiki/Q11785332","display_name":"Monte Carlo tree search","level":3,"score":0.5293170809745789},{"id":"https://openalex.org/C57830394","wikidata":"https://www.wikidata.org/wiki/Q278079","display_name":"Posterior probability","level":3,"score":0.5130351781845093},{"id":"https://openalex.org/C19499675","wikidata":"https://www.wikidata.org/wiki/Q232207","display_name":"Monte Carlo method","level":2,"score":0.48849308490753174},{"id":"https://openalex.org/C169214877","wikidata":"https://www.wikidata.org/wiki/Q981016","display_name":"Dirichlet distribution","level":3,"score":0.48630866408348083},{"id":"https://openalex.org/C113174947","wikidata":"https://www.wikidata.org/wiki/Q2859736","display_name":"Tree (set theory)","level":2,"score":0.4382099211215973},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.42457765340805054},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3908610939979553},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3371732831001282},{"id":"https://openalex.org/C107673813","wikidata":"https://www.wikidata.org/wiki/Q812534","display_name":"Bayesian probability","level":2,"score":0.33237600326538086},{"id":"https://openalex.org/C163836022","wikidata":"https://www.wikidata.org/wiki/Q6771326","display_name":"Markov model","level":3,"score":0.1960829496383667},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.18971103429794312},{"id":"https://openalex.org/C98763669","wikidata":"https://www.wikidata.org/wiki/Q176645","display_name":"Markov chain","level":2,"score":0.18177738785743713},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.10560441017150879},{"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/C182310444","wikidata":"https://www.wikidata.org/wiki/Q1332643","display_name":"Boundary value problem","level":2,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1007/s10489-018-1248-5","is_oa":false,"landing_page_url":"https://doi.org/10.1007/s10489-018-1248-5","pdf_url":null,"source":{"id":"https://openalex.org/S74726891","display_name":"Applied Intelligence","issn_l":"0924-669X","issn":["0924-669X","1573-7497"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Applied Intelligence","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G3037415366","display_name":"\u670d\u52a1\u673a\u5668\u4eba\u52a8\u6001\u8ba4\u77e5\u673a\u5236\u7814\u7a76\u4e0e\u539f\u578b\u7cfb\u7edf\u5b9e\u9a8c","funder_award_id":"61175057","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":91,"referenced_works":["https://openalex.org/W108082272","https://openalex.org/W129361833","https://openalex.org/W130797843","https://openalex.org/W148122774","https://openalex.org/W160961942","https://openalex.org/W178169250","https://openalex.org/W620038288","https://openalex.org/W1498235675","https://openalex.org/W1532688806","https://openalex.org/W1537258144","https://openalex.org/W1556274146","https://openalex.org/W1581055761","https://openalex.org/W1581952794","https://openalex.org/W1591803298","https://openalex.org/W1592076897","https://openalex.org/W1619459736","https://openalex.org/W1625390266","https://openalex.org/W1792278168","https://openalex.org/W1911551976","https://openalex.org/W1921016406","https://openalex.org/W1928468454","https://openalex.org/W1992876208","https://openalex.org/W1997840820","https://openalex.org/W2009533501","https://openalex.org/W2009551863","https://openalex.org/W2020135152","https://openalex.org/W2034713309","https://openalex.org/W2039522160","https://openalex.org/W2049934117","https://openalex.org/W2071814471","https://openalex.org/W2098613108","https://openalex.org/W2099430963","https://openalex.org/W2099619710","https://openalex.org/W2105757562","https://openalex.org/W2106606323","https://openalex.org/W2107726111","https://openalex.org/W2108114251","https://openalex.org/W2108738385","https://openalex.org/W2108794978","https://openalex.org/W2110632090","https://openalex.org/W2111764152","https://openalex.org/W2111971073","https://openalex.org/W2112583639","https://openalex.org/W2113889826","https://openalex.org/W2116708838","https://openalex.org/W2117667273","https://openalex.org/W2119567691","https://openalex.org/W2121517924","https://openalex.org/W2121863487","https://openalex.org/W2122659384","https://openalex.org/W2124595631","https://openalex.org/W2126316555","https://openalex.org/W2132854830","https://openalex.org/W2134802714","https://openalex.org/W2140495055","https://openalex.org/W2141645258","https://openalex.org/W2144913588","https://openalex.org/W2157136665","https://openalex.org/W2158319693","https://openalex.org/W2168359464","https://openalex.org/W2168405694","https://openalex.org/W2171084228","https://openalex.org/W2185653305","https://openalex.org/W2209959171","https://openalex.org/W2215257094","https://openalex.org/W2257979135","https://openalex.org/W2294604761","https://openalex.org/W2295500160","https://openalex.org/W2334782222","https://openalex.org/W2341171179","https://openalex.org/W2341906087","https://openalex.org/W2397893331","https://openalex.org/W2399576838","https://openalex.org/W2401854627","https://openalex.org/W2407383140","https://openalex.org/W2500381110","https://openalex.org/W2522635871","https://openalex.org/W2525579820","https://openalex.org/W2561675875","https://openalex.org/W2572919868","https://openalex.org/W2606126444","https://openalex.org/W2617704515","https://openalex.org/W2766447205","https://openalex.org/W2949764112","https://openalex.org/W2950929549","https://openalex.org/W3016548437","https://openalex.org/W3023151133","https://openalex.org/W3152507489","https://openalex.org/W4214717370","https://openalex.org/W4249186015","https://openalex.org/W4294558384"],"related_works":["https://openalex.org/W1602838358","https://openalex.org/W3114268180","https://openalex.org/W4287586899","https://openalex.org/W3121358068","https://openalex.org/W3124223110","https://openalex.org/W91819771","https://openalex.org/W2972570039","https://openalex.org/W4386143234","https://openalex.org/W2172000475","https://openalex.org/W2885769506"],"abstract_inverted_index":null,"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":3},{"year":2023,"cited_by_count":2}],"updated_date":"2026-06-06T09:05:17.133730","created_date":"2025-10-10T00:00:00"}
