{"id":"https://openalex.org/W2773347582","doi":"https://doi.org/10.1109/iros.2017.8202146","title":"Approximating reachable belief points in POMDPs","display_name":"Approximating reachable belief points in POMDPs","publication_year":2017,"publication_date":"2017-09-01","ids":{"openalex":"https://openalex.org/W2773347582","doi":"https://doi.org/10.1109/iros.2017.8202146","mag":"2773347582"},"language":"en","primary_location":{"id":"doi:10.1109/iros.2017.8202146","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iros.2017.8202146","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2017 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)","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/A5013249239","display_name":"Kyle Hollins Wray","orcid":"https://orcid.org/0000-0001-6986-9941"},"institutions":[{"id":"https://openalex.org/I24603500","display_name":"University of Massachusetts Amherst","ror":"https://ror.org/0072zz521","country_code":"US","type":"education","lineage":["https://openalex.org/I24603500"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Kyle Hollins Wray","raw_affiliation_strings":["College of Information and Computer Sciences, University of Massachusetts, Amherst, MA, US"],"affiliations":[{"raw_affiliation_string":"College of Information and Computer Sciences, University of Massachusetts, Amherst, MA, US","institution_ids":["https://openalex.org/I24603500"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5027224308","display_name":"Shlomo Zilberstein","orcid":"https://orcid.org/0000-0001-9817-7848"},"institutions":[{"id":"https://openalex.org/I24603500","display_name":"University of Massachusetts Amherst","ror":"https://ror.org/0072zz521","country_code":"US","type":"education","lineage":["https://openalex.org/I24603500"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Shlomo Zilberstein","raw_affiliation_strings":["College of Information and Computer Sciences, University of Massachusetts, Amherst, MA, US"],"affiliations":[{"raw_affiliation_string":"College of Information and Computer Sciences, University of Massachusetts, Amherst, MA, US","institution_ids":["https://openalex.org/I24603500"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5013249239"],"corresponding_institution_ids":["https://openalex.org/I24603500"],"apc_list":null,"apc_paid":null,"fwci":0.5851,"has_fulltext":false,"cited_by_count":6,"citation_normalized_percentile":{"value":0.76735449,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":97},"biblio":{"volume":"23","issue":null,"first_page":"117","last_page":"122"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11303","display_name":"Bayesian Modeling and Causal Inference","score":0.9979000091552734,"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/T11303","display_name":"Bayesian Modeling and Causal Inference","score":0.9979000091552734,"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/T10711","display_name":"Target Tracking and Data Fusion in Sensor Networks","score":0.9957000017166138,"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":0.9907000064849854,"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/correctness","display_name":"Correctness","score":0.864073634147644},{"id":"https://openalex.org/keywords/markov-decision-process","display_name":"Markov decision process","score":0.8077716827392578},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.646512508392334},{"id":"https://openalex.org/keywords/observable","display_name":"Observable","score":0.6291711330413818},{"id":"https://openalex.org/keywords/upper-and-lower-bounds","display_name":"Upper and lower bounds","score":0.6015197038650513},{"id":"https://openalex.org/keywords/zero","display_name":"Zero (linguistics)","score":0.5498235821723938},{"id":"https://openalex.org/keywords/point","display_name":"Point (geometry)","score":0.47027188539505005},{"id":"https://openalex.org/keywords/approximation-error","display_name":"Approximation error","score":0.4412387013435364},{"id":"https://openalex.org/keywords/expected-value","display_name":"Expected value","score":0.4280416965484619},{"id":"https://openalex.org/keywords/mathematical-optimization","display_name":"Mathematical optimization","score":0.4213581383228302},{"id":"https://openalex.org/keywords/markov-process","display_name":"Markov process","score":0.41636019945144653},{"id":"https://openalex.org/keywords/approximation-algorithm","display_name":"Approximation algorithm","score":0.41469353437423706},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.41314855217933655},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.30372676253318787},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.08075901865959167}],"concepts":[{"id":"https://openalex.org/C55439883","wikidata":"https://www.wikidata.org/wiki/Q360812","display_name":"Correctness","level":2,"score":0.864073634147644},{"id":"https://openalex.org/C106189395","wikidata":"https://www.wikidata.org/wiki/Q176789","display_name":"Markov decision process","level":3,"score":0.8077716827392578},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.646512508392334},{"id":"https://openalex.org/C32848918","wikidata":"https://www.wikidata.org/wiki/Q845789","display_name":"Observable","level":2,"score":0.6291711330413818},{"id":"https://openalex.org/C77553402","wikidata":"https://www.wikidata.org/wiki/Q13222579","display_name":"Upper and lower bounds","level":2,"score":0.6015197038650513},{"id":"https://openalex.org/C2780813799","wikidata":"https://www.wikidata.org/wiki/Q3274237","display_name":"Zero (linguistics)","level":2,"score":0.5498235821723938},{"id":"https://openalex.org/C28719098","wikidata":"https://www.wikidata.org/wiki/Q44946","display_name":"Point (geometry)","level":2,"score":0.47027188539505005},{"id":"https://openalex.org/C122383733","wikidata":"https://www.wikidata.org/wiki/Q865920","display_name":"Approximation error","level":2,"score":0.4412387013435364},{"id":"https://openalex.org/C141042865","wikidata":"https://www.wikidata.org/wiki/Q200125","display_name":"Expected value","level":2,"score":0.4280416965484619},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.4213581383228302},{"id":"https://openalex.org/C159886148","wikidata":"https://www.wikidata.org/wiki/Q176645","display_name":"Markov process","level":2,"score":0.41636019945144653},{"id":"https://openalex.org/C148764684","wikidata":"https://www.wikidata.org/wiki/Q621751","display_name":"Approximation algorithm","level":2,"score":0.41469353437423706},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.41314855217933655},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.30372676253318787},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.08075901865959167},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"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/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","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}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/iros.2017.8202146","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iros.2017.8202146","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2017 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Peace, Justice and strong institutions","id":"https://metadata.un.org/sdg/16","score":0.7599999904632568}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":34,"referenced_works":["https://openalex.org/W45766481","https://openalex.org/W77538448","https://openalex.org/W1532688806","https://openalex.org/W1533557532","https://openalex.org/W1967769980","https://openalex.org/W2010358969","https://openalex.org/W2047990226","https://openalex.org/W2055921164","https://openalex.org/W2101421095","https://openalex.org/W2107696078","https://openalex.org/W2110962519","https://openalex.org/W2116753650","https://openalex.org/W2134802714","https://openalex.org/W2138089556","https://openalex.org/W2144794447","https://openalex.org/W2149476049","https://openalex.org/W2152706713","https://openalex.org/W2158907787","https://openalex.org/W2168359464","https://openalex.org/W2177060007","https://openalex.org/W2259075191","https://openalex.org/W2739957299","https://openalex.org/W2903040101","https://openalex.org/W3101822862","https://openalex.org/W6601831483","https://openalex.org/W6603152148","https://openalex.org/W6631864160","https://openalex.org/W6631931890","https://openalex.org/W6679977494","https://openalex.org/W6680602851","https://openalex.org/W6681472862","https://openalex.org/W6682102841","https://openalex.org/W6692580597","https://openalex.org/W6757277003"],"related_works":["https://openalex.org/W131709709","https://openalex.org/W2110817230","https://openalex.org/W1994680671","https://openalex.org/W3091355678","https://openalex.org/W1606488336","https://openalex.org/W1988569331","https://openalex.org/W189995875","https://openalex.org/W4255193494","https://openalex.org/W2284958355","https://openalex.org/W2962894463"],"abstract_inverted_index":{"We":[0,48,108],"propose":[1],"an":[2,103],"algorithm":[3,74,94],"called":[4],"\u03c3-approximation":[5,59],"that":[6,91],"compresses":[7],"the":[8,40,50,58,63,73,80,86,93],"non-zero":[9,43,83],"values":[10,44,84],"of":[11,42,82,105],"beliefs":[12],"for":[13,85,117],"partially":[14],"observable":[15],"Markov":[16],"decision":[17],"processes":[18],"(POMDPs)":[19],"in":[20],"order":[21,104],"to":[22],"improve":[23],"performance":[24],"and":[25,52,120],"reduce":[26],"memory":[27],"usage.":[28],"Specifically,":[29],"we":[30,99],"approximate":[31],"individual":[32],"belief":[33],"vectors":[34],"with":[35,62,96,112,124],"a":[36,53,113],"fixed":[37],"bound":[38,56],"on":[39,75],"number":[41,81],"they":[45],"may":[46],"contain.":[47],"prove":[49],"correctness":[51],"strong":[54],"error":[55],"when":[57,92],"is":[60],"used":[61,95],"point-based":[64],"value":[65],"iteration":[66],"(PBVI)":[67],"family":[68],"algorithms.":[69],"An":[70],"analysis":[71],"compares":[72],"six":[76],"larger":[77],"domains,":[78],"varying":[79],"\u03c3-approximation.":[87],"Results":[88],"clearly":[89],"demonstrate":[90],"PBVI":[97],"(\u03c3-PBVI),":[98],"can":[100],"achieve":[101],"over":[102],"magnitude":[106],"improvement.":[107],"ground":[109],"our":[110],"claims":[111],"full":[114],"robotic":[115],"implementation":[116],"simultaneous":[118],"navigation":[119],"localization":[121],"using":[122],"POMDPs":[123],"\u03c3-PBVI.":[125]},"counts_by_year":[{"year":2021,"cited_by_count":3},{"year":2020,"cited_by_count":1},{"year":2019,"cited_by_count":1},{"year":2018,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}