{"id":"https://openalex.org/W4406612515","doi":"https://doi.org/10.1109/wsc63780.2024.10838839","title":"Multi Agent Rollout for Bayesian Optimization","display_name":"Multi Agent Rollout for Bayesian Optimization","publication_year":2024,"publication_date":"2024-12-15","ids":{"openalex":"https://openalex.org/W4406612515","doi":"https://doi.org/10.1109/wsc63780.2024.10838839"},"language":"en","primary_location":{"id":"doi:10.1109/wsc63780.2024.10838839","is_oa":false,"landing_page_url":"https://doi.org/10.1109/wsc63780.2024.10838839","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 Winter Simulation Conference (WSC)","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/A5115947382","display_name":"Shyam Sundar Nambiraja","orcid":null},"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":true,"raw_author_name":"Shyam Sundar Nambiraja","raw_affiliation_strings":["School of Computing and Augmented Intelligence, Arizona State University,Tempe,AZ,USA"],"affiliations":[{"raw_affiliation_string":"School of Computing and Augmented Intelligence, Arizona State University,Tempe,AZ,USA","institution_ids":["https://openalex.org/I55732556"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5049158387","display_name":"Giulia Pedrielli","orcid":"https://orcid.org/0000-0001-6726-9790"},"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":"Giulia Pedrielli","raw_affiliation_strings":["School of Computing and Augmented Intelligence, Arizona State University,Tempe,AZ,USA"],"affiliations":[{"raw_affiliation_string":"School of Computing and Augmented Intelligence, 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/A5115947382"],"corresponding_institution_ids":["https://openalex.org/I55732556"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.32378145,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"3518","last_page":"3529"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11195","display_name":"Simulation Techniques and Applications","score":0.923799991607666,"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"}},"topics":[{"id":"https://openalex.org/T11195","display_name":"Simulation Techniques and Applications","score":0.923799991607666,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6529654860496521},{"id":"https://openalex.org/keywords/bayesian-probability","display_name":"Bayesian probability","score":0.5875789523124695},{"id":"https://openalex.org/keywords/bayesian-optimization","display_name":"Bayesian optimization","score":0.5727197527885437},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3428424596786499}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6529654860496521},{"id":"https://openalex.org/C107673813","wikidata":"https://www.wikidata.org/wiki/Q812534","display_name":"Bayesian probability","level":2,"score":0.5875789523124695},{"id":"https://openalex.org/C2778049539","wikidata":"https://www.wikidata.org/wiki/Q17002908","display_name":"Bayesian optimization","level":2,"score":0.5727197527885437},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3428424596786499}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/wsc63780.2024.10838839","is_oa":false,"landing_page_url":"https://doi.org/10.1109/wsc63780.2024.10838839","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 Winter Simulation Conference (WSC)","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":22,"referenced_works":["https://openalex.org/W414567873","https://openalex.org/W1480330138","https://openalex.org/W1510052597","https://openalex.org/W2151604161","https://openalex.org/W2945677399","https://openalex.org/W3011445295","https://openalex.org/W3046086400","https://openalex.org/W3205889124","https://openalex.org/W4225993418","https://openalex.org/W4249753629","https://openalex.org/W4388910220","https://openalex.org/W4389667083","https://openalex.org/W6680331187","https://openalex.org/W6748587240","https://openalex.org/W6766900132","https://openalex.org/W6768423395","https://openalex.org/W6774326721","https://openalex.org/W6779840123","https://openalex.org/W6779994930","https://openalex.org/W6791245825","https://openalex.org/W6838867289","https://openalex.org/W6845734913"],"related_works":["https://openalex.org/W4391375266","https://openalex.org/W2899084033","https://openalex.org/W2748952813","https://openalex.org/W3106461837","https://openalex.org/W2390279801","https://openalex.org/W4391913857","https://openalex.org/W2358668433","https://openalex.org/W4396701345","https://openalex.org/W2376932109","https://openalex.org/W4401858220"],"abstract_inverted_index":{"Solving":[0],"black-box":[1],"global":[2],"optimization":[3,14,17,26,76],"problems":[4],"efficiently":[5],"across":[6],"domains":[7],"remains":[8],"challenging":[9],"especially":[10],"for":[11,88],"large":[12,38],"scale":[13,39],"problems.":[15],"Bayesian":[16,75],"has":[18],"obtained":[19],"important":[20,61],"success":[21],"as":[22],"a":[23,69,114,135],"black":[24],"box":[25],"technique":[27],"based":[28],"on":[29,146],"surrogates,":[30],"but":[31],"it":[32],"still":[33],"suffers":[34],"when":[35],"applied":[36],"to":[37,56,93],"heterogeneous":[40],"landscapes.":[41],"Recent":[42],"approaches":[43],"have":[44],"proposed":[45],"non-myopic":[46],"approximations":[47],"and":[48],"partitioning":[49,109],"of":[50,63,74,86,116,134,142],"the":[51,64,80,110,117],"input":[52,81],"domain":[53,82],"into":[54],"subregions":[55],"prioritize":[57,125],"regions":[58],"that":[59,78,128],"capture":[60],"areas":[62],"solution":[65],"space.":[66],"We":[67],"propose":[68],"Multi":[70],"Agent":[71],"Rollout":[72],"formulation":[73],"(MAroBO)":[77],"partitions":[79],"among":[83],"finite":[84],"set":[85],"agents":[87,103,123],"distributed":[89],"sampling.":[90],"In":[91],"addition":[92],"selecting":[94],"candidate":[95,126],"samples":[96,127],"from":[97],"their":[98],"respective":[99],"sub":[100,111],"regions,":[101],"these":[102,122],"also":[104],"influence":[105],"each":[106],"other":[107],"in":[108,132],"regions.":[112],"Consequently,":[113],"portion":[115],"function":[118],"is":[119,144],"optimized":[120],"by":[121],"which":[124],"don't":[129],"undermine":[130],"exploration":[131],"favor":[133],"single":[136],"step":[137],"greedy":[138],"exploitation.":[139],"The":[140],"efficacy":[141],"MAroBO":[143],"demonstrated":[145],"synthetic":[147],"test":[148],"functions.":[149]},"counts_by_year":[],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
