{"id":"https://openalex.org/W4396822241","doi":"https://doi.org/10.48550/arxiv.2405.05662","title":"Approximate Dec-POMDP Solving Using Multi-Agent A*","display_name":"Approximate Dec-POMDP Solving Using Multi-Agent A*","publication_year":2024,"publication_date":"2024-05-09","ids":{"openalex":"https://openalex.org/W4396822241","doi":"https://doi.org/10.48550/arxiv.2405.05662"},"language":"en","primary_location":{"id":"pmh:oai:arXiv.org:2405.05662","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2405.05662","pdf_url":"https://arxiv.org/pdf/2405.05662","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"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":null,"raw_type":"text"},"type":"preprint","indexed_in":["arxiv","datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2405.05662","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5041856292","display_name":"W.J. Koops","orcid":"https://orcid.org/0000-0001-9945-1992"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Koops, Wietze","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5018941708","display_name":"Sebastian Junges","orcid":"https://orcid.org/0000-0003-0978-8466"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Junges, Sebastian","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5012669709","display_name":"Nils Jansen","orcid":"https://orcid.org/0000-0003-1318-8973"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Jansen, Nils","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":true,"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/T12546","display_name":"Smart Parking Systems Research","score":0.9562000036239624,"subfield":{"id":"https://openalex.org/subfields/2215","display_name":"Building and Construction"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T12546","display_name":"Smart Parking Systems Research","score":0.9562000036239624,"subfield":{"id":"https://openalex.org/subfields/2215","display_name":"Building and Construction"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10567","display_name":"Vehicle Routing Optimization Methods","score":0.902400016784668,"subfield":{"id":"https://openalex.org/subfields/2209","display_name":"Industrial and Manufacturing 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/partially-observable-markov-decision-process","display_name":"Partially observable Markov decision process","score":0.6618906259536743},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5244600772857666},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.35745537281036377},{"id":"https://openalex.org/keywords/mathematical-optimization","display_name":"Mathematical optimization","score":0.340136855840683},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.28035831451416016},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.18838146328926086},{"id":"https://openalex.org/keywords/markov-chain","display_name":"Markov chain","score":0.11645853519439697}],"concepts":[{"id":"https://openalex.org/C17098449","wikidata":"https://www.wikidata.org/wiki/Q176814","display_name":"Partially observable Markov decision process","level":4,"score":0.6618906259536743},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5244600772857666},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.35745537281036377},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.340136855840683},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.28035831451416016},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.18838146328926086},{"id":"https://openalex.org/C98763669","wikidata":"https://www.wikidata.org/wiki/Q176645","display_name":"Markov chain","level":2,"score":0.11645853519439697},{"id":"https://openalex.org/C163836022","wikidata":"https://www.wikidata.org/wiki/Q6771326","display_name":"Markov model","level":3,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"pmh:oai:arXiv.org:2405.05662","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2405.05662","pdf_url":"https://arxiv.org/pdf/2405.05662","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"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":null,"raw_type":"text"},{"id":"doi:10.48550/arxiv.2405.05662","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2405.05662","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"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":"pmh:oai:arXiv.org:2405.05662","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2405.05662","pdf_url":"https://arxiv.org/pdf/2405.05662","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"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":null,"raw_type":"text"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G2039356335","display_name":null,"funder_award_id":"1160.18.238","funder_id":"https://openalex.org/F4320321800","funder_display_name":"Nederlandse Organisatie voor Wetenschappelijk Onderzoek"},{"id":"https://openalex.org/G4371345817","display_name":"PrimaVera: Predictive maintenance for Very effective asset management","funder_award_id":"NWA.1160.18.238","funder_id":"https://openalex.org/F4320321800","funder_display_name":"Nederlandse Organisatie voor Wetenschappelijk Onderzoek"}],"funders":[{"id":"https://openalex.org/F4320321800","display_name":"Nederlandse Organisatie voor Wetenschappelijk Onderzoek","ror":"https://ror.org/04jsz6e67"}],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4396822241.pdf","grobid_xml":"https://content.openalex.org/works/W4396822241.grobid-xml"},"referenced_works_count":0,"referenced_works":[],"related_works":["https://openalex.org/W4391375266","https://openalex.org/W2748952813","https://openalex.org/W2123651102","https://openalex.org/W2953027552","https://openalex.org/W2287992105","https://openalex.org/W2570299561","https://openalex.org/W2392831491","https://openalex.org/W2117555338","https://openalex.org/W2130339357","https://openalex.org/W1512585804"],"abstract_inverted_index":{"We":[0],"present":[1],"an":[2,69],"A*-based":[3],"algorithm":[4,71],"to":[5,14,54],"compute":[6],"policies":[7],"for":[8,21,58,76],"finite-horizon":[9],"Dec-POMDPs.":[10],"Our":[11,49,104],"goal":[12],"is":[13,88],"sacrifice":[15],"optimality":[16],"in":[17],"favor":[18],"of":[19,27,101,111],"scalability":[20,110],"larger":[22],"horizons.":[23,84],"The":[24,85],"main":[25,86],"ingredients":[26],"our":[28],"approach":[29],"are":[30],"(1)":[31],"using":[32,45],"clustered":[33],"sliding":[34],"window":[35],"memory,":[36],"(2)":[37],"pruning":[38],"the":[39,55,77,95,99,107,112],"A*":[40,47,70],"search":[41],"tree,":[42],"and":[43,109],"(3)":[44],"novel":[46],"heuristics.":[48],"experiments":[50,105],"show":[51],"competitive":[52],"performance":[53],"state-of-the-art.":[56],"Moreover,":[57],"multiple":[59],"benchmarks,":[60],"we":[61,67],"achieve":[62],"superior":[63],"performance.":[64],"In":[65],"addition,":[66],"provide":[68],"that":[72,92],"finds":[73],"upper":[74],"bounds":[75],"optimum,":[78],"tailored":[79],"towards":[80],"problems":[81],"with":[82],"long":[83],"ingredient":[87],"a":[89],"new":[90],"heuristic":[91],"periodically":[93],"reveals":[94],"state,":[96],"thereby":[97],"limiting":[98],"number":[100],"reachable":[102],"beliefs.":[103],"demonstrate":[106],"efficacy":[108],"approach.":[113]},"counts_by_year":[],"updated_date":"2026-08-26T07:47:46.906454","created_date":"2025-10-10T00:00:00"}