{"id":"https://openalex.org/W2890940627","doi":"https://doi.org/10.48550/arxiv.1809.01220","title":"Vulcan: A Monte Carlo Algorithm for Large Chance Constrained MDPs with Risk Bounding Functions","display_name":"Vulcan: A Monte Carlo Algorithm for Large Chance Constrained MDPs with Risk Bounding Functions","publication_year":2018,"publication_date":"2018-09-04","ids":{"openalex":"https://openalex.org/W2890940627","doi":"https://doi.org/10.48550/arxiv.1809.01220","mag":"2890940627"},"language":"en","primary_location":{"id":"pmh:oai:arXiv.org:1809.01220","doi":null,"is_oa":true,"landing_page_url":"http://arxiv.org/abs/1809.01220","pdf_url":"https://arxiv.org/pdf/1809.01220","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,"listed_in":[],"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"},"volume":null,"type":"preprint","indexed_in":["arxiv","datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/1809.01220","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5007870460","display_name":"B. Ayton","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I63966007","display_name":"Massachusetts Institute of Technology","ror":"https://ror.org/042nb2s44","country_code":"US","type":"education","lineage":["https://openalex.org/I63966007"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Ayton, Benjamin J","raw_affiliation_strings":["Computer Science and Artificial Intelligence Laboratory , Massachusetts Institute of Technology 32 Vassar St , Cambridge MA , 02139"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Computer Science and Artificial Intelligence Laboratory , Massachusetts Institute of Technology 32 Vassar St , Cambridge MA , 02139","institution_ids":["https://openalex.org/I63966007"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5101709620","display_name":"Brian Charles Williams","orcid":"https://orcid.org/0000-0002-1057-3940","observed_orcids":["https://orcid.org/0000-0002-1057-3940"]},"institutions":[{"id":"https://openalex.org/I63966007","display_name":"Massachusetts Institute of Technology","ror":"https://ror.org/042nb2s44","country_code":"US","type":"education","lineage":["https://openalex.org/I63966007"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Williams, Brian C","raw_affiliation_strings":["Computer Science and Artificial Intelligence Laboratory , Massachusetts Institute of Technology 32 Vassar St , Cambridge MA , 02139"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Computer Science and Artificial Intelligence Laboratory , Massachusetts Institute of Technology 32 Vassar St , Cambridge MA , 02139","institution_ids":["https://openalex.org/I63966007"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I63966007"],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":true,"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":0.6660000085830688,"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":0.6660000085830688,"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/T10906","display_name":"AI-based Problem Solving and Planning","score":0.12460000067949295,"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/T10586","display_name":"Robotic Path Planning Algorithms","score":0.048500001430511475,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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/vulcan","display_name":"Vulcan","score":0.5180000066757202},{"id":"https://openalex.org/keywords/monte-carlo-tree-search","display_name":"Monte Carlo tree search","score":0.9269999861717224},{"id":"https://openalex.org/keywords/failure-probability","display_name":"failure probability","score":0.7820000052452087},{"id":"https://openalex.org/keywords/anytime-algorithms","display_name":"anytime algorithms","score":0.5809999704360962},{"id":"https://openalex.org/keywords/large-state-spaces","display_name":"large state spaces","score":0.753000020980835},{"id":"https://openalex.org/keywords/planning-under-uncertainty","display_name":"planning under uncertainty","score":0.531000018119812},{"id":"https://openalex.org/keywords/suboptimal-policies","display_name":"suboptimal policies","score":0.5360000133514404}],"concepts":[{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.6876039505004883},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6329160928726196},{"id":"https://openalex.org/C127705205","wikidata":"https://www.wikidata.org/wiki/Q5748245","display_name":"Heuristics","level":2,"score":0.6108835935592651},{"id":"https://openalex.org/C63584917","wikidata":"https://www.wikidata.org/wiki/Q333286","display_name":"Bounding overwatch","level":2,"score":0.5936194062232971},{"id":"https://openalex.org/C46149586","wikidata":"https://www.wikidata.org/wiki/Q11785332","display_name":"Monte Carlo tree search","level":3,"score":0.5877825021743774},{"id":"https://openalex.org/C106189395","wikidata":"https://www.wikidata.org/wiki/Q176789","display_name":"Markov decision process","level":3,"score":0.5640255212783813},{"id":"https://openalex.org/C2776036281","wikidata":"https://www.wikidata.org/wiki/Q48769818","display_name":"Constraint (computer-aided design)","level":2,"score":0.5501787662506104},{"id":"https://openalex.org/C19499675","wikidata":"https://www.wikidata.org/wiki/Q232207","display_name":"Monte Carlo method","level":2,"score":0.5287135243415833},{"id":"https://openalex.org/C72434380","wikidata":"https://www.wikidata.org/wiki/Q230930","display_name":"State space","level":2,"score":0.5168271660804749},{"id":"https://openalex.org/C173801870","wikidata":"https://www.wikidata.org/wiki/Q201413","display_name":"Heuristic","level":2,"score":0.4888138473033905},{"id":"https://openalex.org/C48103436","wikidata":"https://www.wikidata.org/wiki/Q599031","display_name":"State (computer science)","level":2,"score":0.4346637725830078},{"id":"https://openalex.org/C34388435","wikidata":"https://www.wikidata.org/wiki/Q2267362","display_name":"Bounded function","level":2,"score":0.4275491237640381},{"id":"https://openalex.org/C159886148","wikidata":"https://www.wikidata.org/wiki/Q176645","display_name":"Markov process","level":2,"score":0.35251691937446594},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.26562774181365967},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.25555986166000366},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.12489235401153564},{"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/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.0}],"mesh":[],"locations_count":3,"locations":[{"id":"pmh:oai:arXiv.org:1809.01220","doi":null,"is_oa":true,"landing_page_url":"http://arxiv.org/abs/1809.01220","pdf_url":"https://arxiv.org/pdf/1809.01220","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,"listed_in":[],"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":"mag:2890940627","doi":null,"is_oa":true,"landing_page_url":"https://arxiv.org/pdf/1809.01220.pdf","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,"listed_in":[],"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":"arXiv (Cornell University)","raw_type":null},{"id":"doi:10.48550/arxiv.1809.01220","doi":"https://doi.org/10.48550/arxiv.1809.01220","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.1809.01220","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,"listed_in":[],"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:1809.01220","doi":null,"is_oa":true,"landing_page_url":"http://arxiv.org/abs/1809.01220","pdf_url":"https://arxiv.org/pdf/1809.01220","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,"listed_in":[],"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":[],"sustainable_development_goals_aurora":[{"score":0.7900000214576721,"display_name":"Peace, justice, and strong institutions","id":"https://metadata.un.org/sdg/16"}],"study_designs":[],"awards":[{"id":"https://openalex.org/G1674482446","display_name":null,"funder_award_id":"EM09079","funder_id":"https://openalex.org/F4320307811","funder_display_name":"Exxon Mobil Corporation"}],"funders":[{"id":"https://openalex.org/F4320307811","display_name":"Exxon Mobil Corporation","ror":"https://ror.org/01xcepn55"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":20,"referenced_works":["https://openalex.org/W1518931405","https://openalex.org/W1597160459","https://openalex.org/W1625390266","https://openalex.org/W1746819321","https://openalex.org/W1979882689","https://openalex.org/W2051483500","https://openalex.org/W2055156725","https://openalex.org/W2077789482","https://openalex.org/W2110790702","https://openalex.org/W2119567691","https://openalex.org/W2126316555","https://openalex.org/W2139809908","https://openalex.org/W2147867446","https://openalex.org/W2162087735","https://openalex.org/W2168405694","https://openalex.org/W2171369888","https://openalex.org/W2257979135","https://openalex.org/W2317700292","https://openalex.org/W2338861484","https://openalex.org/W3106238320"],"related_works":["https://openalex.org/W3201837228","https://openalex.org/W2904903320","https://openalex.org/W1144593952","https://openalex.org/W2080717363","https://openalex.org/W3083392746","https://openalex.org/W3199073031","https://openalex.org/W2966584725","https://openalex.org/W2604677816","https://openalex.org/W2554915786","https://openalex.org/W52833132","https://openalex.org/W10564759","https://openalex.org/W2189416168","https://openalex.org/W2949417159","https://openalex.org/W3023151133","https://openalex.org/W2594219130","https://openalex.org/W2909648661","https://openalex.org/W1189345","https://openalex.org/W3047813923","https://openalex.org/W2614019236","https://openalex.org/W202180931"],"abstract_inverted_index":{"Chance":[0],"Constrained":[1],"Markov":[2],"Decision":[3],"Processes":[4],"maximize":[5],"reward":[6,97],"subject":[7],"to":[8,38,44,52,71,78,110,153,159,165,171,195,238],"a":[9,55,72,85,88,99,104,115,218,224,231,241,246],"bounded":[10],"probability":[11,61,93],"of":[12,46,62,67,87,94,197,230],"failure,":[13],"and":[14,118,177,190,204,220],"have":[15,30,35],"been":[16,36],"frequently":[17],"applied":[18,109,164],"for":[19,217,240],"planning":[20],"with":[21,42,223,248],"potentially":[22],"dangerous":[23],"outcomes":[24],"or":[25,34],"unknown":[26],"environments.":[27],"Solution":[28],"algorithms":[29],"required":[31],"strong":[32],"heuristics":[33],"limited":[37],"relatively":[39],"small":[40],"problems":[41,138,166],"up":[43],"millions":[45],"states,":[47],"because":[48],"the":[49,60,65,68,122,133,173,215,228],"optimal":[50],"action":[51],"take":[53],"from":[54],"given":[56],"state":[57,112,175],"depends":[58],"on":[59,227],"failure":[63,95],"in":[64,114,132,151,182,245,252],"rest":[66],"policy,":[69],"leading":[70],"coupled":[73],"problem":[74],"that":[75,90,106,121,136,188],"is":[76,169],"difficult":[77],"solve.":[79],"In":[80],"this":[81],"paper":[82],"we":[83,235],"examine":[84],"generalization":[86],"CCMDP":[89,247],"trades":[91],"off":[92],"against":[96],"through":[98],"functional":[100],"relationship.":[101],"We":[102,143,186],"derive":[103],"constraint":[105,124,150],"can":[107,139,162],"be":[108,126,140,163,180],"each":[111],"history":[113],"policy":[116,244],"individually,":[117],"which":[119,147],"guarantees":[120],"chance":[123,242],"will":[125],"satisfied.":[127],"The":[128],"approach":[129],"decouples":[130],"states":[131,251],"CCMDP,":[134],"so":[135],"large":[137],"solved":[141],"efficiently.":[142],"then":[144],"introduce":[145],"Vulcan,":[146],"uses":[148],"our":[149],"order":[152,229],"apply":[154],"Monte":[155],"Carlo":[156],"Tree":[157],"Search":[158],"CCMDPs.":[160],"Vulcan":[161,189,237],"where":[167],"it":[168],"unfeasible":[170],"generate":[172],"entire":[174],"space,":[176],"policies":[178],"must":[179],"returned":[181],"an":[183],"anytime":[184],"manner.":[185],"show":[187],"its":[191],"variants":[192],"run":[193],"tens":[194],"hundreds":[196],"times":[198,207],"faster":[199,208],"than":[200,209],"linear":[201],"programming":[202],"methods,":[203,212],"over":[205,249],"ten":[206],"heuristic":[210],"based":[211],"all":[213],"without":[214],"need":[216],"heuristic,":[219],"returning":[221],"solutions":[222],"mean":[225],"suboptimality":[226],"few":[232],"percent.":[233],"Finally,":[234],"use":[236],"solve":[239],"constrained":[243],"$10^{13}$":[250],"3":[253],"minutes.":[254]},"counts_by_year":[{"year":2023,"cited_by_count":1},{"year":2020,"cited_by_count":2}],"updated_date":"2026-10-14T16:39:01.820549","created_date":"2025-10-10T00:00:00"}