{"id":"https://openalex.org/W4385301254","doi":"https://doi.org/10.1109/iv55152.2023.10186722","title":"Experience Filter: Using Past Experiences on Unseen Tasks or Environments","display_name":"Experience Filter: Using Past Experiences on Unseen Tasks or Environments","publication_year":2023,"publication_date":"2023-06-04","ids":{"openalex":"https://openalex.org/W4385301254","doi":"https://doi.org/10.1109/iv55152.2023.10186722"},"language":"en","primary_location":{"id":"doi:10.1109/iv55152.2023.10186722","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/iv55152.2023.10186722","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 IEEE Intelligent Vehicles Symposium (IV)","raw_type":"proceedings-article"},"type":"conference-paper","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/A5046091617","display_name":"Anil Y\u0131ldiz","orcid":"https://orcid.org/0000-0002-2257-7025"},"institutions":[{"id":"https://openalex.org/I4210137306","display_name":"Stanford Medicine","ror":"https://ror.org/03mtd9a03","country_code":"US","type":"healthcare","lineage":["https://openalex.org/I4210137306","https://openalex.org/I97018004"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Anil Yildiz","raw_affiliation_strings":["Stanford Intelligent Systems Laboratory,Stanford,CA,USA","Stanford Intelligent Systems Laboratory, Stanford, CA, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Stanford Intelligent Systems Laboratory,Stanford,CA,USA","institution_ids":["https://openalex.org/I4210137306"]},{"raw_affiliation_string":"Stanford Intelligent Systems Laboratory, Stanford, CA, USA","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5014381337","display_name":"Esen Yel","orcid":"https://orcid.org/0000-0002-0463-3601"},"institutions":[{"id":"https://openalex.org/I4210137306","display_name":"Stanford Medicine","ror":"https://ror.org/03mtd9a03","country_code":"US","type":"healthcare","lineage":["https://openalex.org/I4210137306","https://openalex.org/I97018004"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Esen Yel","raw_affiliation_strings":["Stanford Intelligent Systems Laboratory,Stanford,CA,USA","Stanford Intelligent Systems Laboratory, Stanford, CA, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Stanford Intelligent Systems Laboratory,Stanford,CA,USA","institution_ids":["https://openalex.org/I4210137306"]},{"raw_affiliation_string":"Stanford Intelligent Systems Laboratory, Stanford, CA, USA","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5003467296","display_name":"Anthony Corso","orcid":"https://orcid.org/0000-0002-4027-0473"},"institutions":[{"id":"https://openalex.org/I4210137306","display_name":"Stanford Medicine","ror":"https://ror.org/03mtd9a03","country_code":"US","type":"healthcare","lineage":["https://openalex.org/I4210137306","https://openalex.org/I97018004"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Anthony L. Corso","raw_affiliation_strings":["Stanford Intelligent Systems Laboratory,Stanford,CA,USA","Stanford Intelligent Systems Laboratory, Stanford, CA, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Stanford Intelligent Systems Laboratory,Stanford,CA,USA","institution_ids":["https://openalex.org/I4210137306"]},{"raw_affiliation_string":"Stanford Intelligent Systems Laboratory, Stanford, CA, USA","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5013249239","display_name":"Kyle Hollins Wray","orcid":"https://orcid.org/0000-0001-6986-9941"},"institutions":[{"id":"https://openalex.org/I4210137306","display_name":"Stanford Medicine","ror":"https://ror.org/03mtd9a03","country_code":"US","type":"healthcare","lineage":["https://openalex.org/I4210137306","https://openalex.org/I97018004"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Kyle H. Wray","raw_affiliation_strings":["Stanford Intelligent Systems Laboratory,Stanford,CA,USA","Stanford Intelligent Systems Laboratory, Stanford, CA, USA","Alliance Innovation Laboratory Silicon Valley, Santa Clara, CA, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Stanford Intelligent Systems Laboratory,Stanford,CA,USA","institution_ids":["https://openalex.org/I4210137306"]},{"raw_affiliation_string":"Stanford Intelligent Systems Laboratory, Stanford, CA, USA","institution_ids":[]},{"raw_affiliation_string":"Alliance Innovation Laboratory Silicon Valley, Santa Clara, CA, USA","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5083359602","display_name":"Stefan Witwicki","orcid":null},"institutions":[{"id":"https://openalex.org/I4210148712","display_name":"Silicon Valley University","ror":"https://ror.org/04jk6hn97","country_code":"US","type":"education","lineage":["https://openalex.org/I4210148712"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Stefan J. Witwicki","raw_affiliation_strings":["Alliance Innovation Laboratory Silicon Valley,Santa Clara,CA,USA","Alliance Innovation Laboratory Silicon Valley, Santa Clara, CA, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Alliance Innovation Laboratory Silicon Valley,Santa Clara,CA,USA","institution_ids":["https://openalex.org/I4210148712"]},{"raw_affiliation_string":"Alliance Innovation Laboratory Silicon Valley, Santa Clara, CA, USA","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5068326377","display_name":"Mykel J. Kochenderfer","orcid":"https://orcid.org/0000-0002-7238-9663"},"institutions":[{"id":"https://openalex.org/I4210137306","display_name":"Stanford Medicine","ror":"https://ror.org/03mtd9a03","country_code":"US","type":"healthcare","lineage":["https://openalex.org/I4210137306","https://openalex.org/I97018004"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Mykel J. Kochenderfer","raw_affiliation_strings":["Stanford Intelligent Systems Laboratory,Stanford,CA,USA","Stanford Intelligent Systems Laboratory, Stanford, CA, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Stanford Intelligent Systems Laboratory,Stanford,CA,USA","institution_ids":["https://openalex.org/I4210137306"]},{"raw_affiliation_string":"Stanford Intelligent Systems Laboratory, Stanford, CA, USA","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":"34","issue":null,"first_page":"1","last_page":"7"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10462","display_name":"Reinforcement Learning in Robotics","score":0.9986000061035156,"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":0.9986000061035156,"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/T11689","display_name":"Adversarial Robustness in Machine Learning","score":0.9932000041007996,"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/T11099","display_name":"Autonomous Vehicle Technology and Safety","score":0.9865000247955322,"subfield":{"id":"https://openalex.org/subfields/2203","display_name":"Automotive 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/computer-science","display_name":"Computer science","score":0.7697879076004028},{"id":"https://openalex.org/keywords/partially-observable-markov-decision-process","display_name":"Partially observable Markov decision process","score":0.7234386205673218},{"id":"https://openalex.org/keywords/fidelity","display_name":"Fidelity","score":0.6545581817626953},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.6412997245788574},{"id":"https://openalex.org/keywords/filter","display_name":"Filter (signal processing)","score":0.5976459383964539},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5855918526649475},{"id":"https://openalex.org/keywords/markov-decision-process","display_name":"Markov decision process","score":0.5773203372955322},{"id":"https://openalex.org/keywords/construct","display_name":"Construct (python library)","score":0.5592030882835388},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.5483397841453552},{"id":"https://openalex.org/keywords/kernel","display_name":"Kernel (algebra)","score":0.5395329594612122},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.5163391828536987},{"id":"https://openalex.org/keywords/reinforcement-learning","display_name":"Reinforcement learning","score":0.46252140402793884},{"id":"https://openalex.org/keywords/parameterized-complexity","display_name":"Parameterized complexity","score":0.42757105827331543},{"id":"https://openalex.org/keywords/markov-process","display_name":"Markov process","score":0.3674992620944977},{"id":"https://openalex.org/keywords/markov-chain","display_name":"Markov chain","score":0.3056056797504425},{"id":"https://openalex.org/keywords/markov-model","display_name":"Markov model","score":0.24523749947547913},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.13326379656791687},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.10744449496269226}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7697879076004028},{"id":"https://openalex.org/C17098449","wikidata":"https://www.wikidata.org/wiki/Q176814","display_name":"Partially observable Markov decision process","level":4,"score":0.7234386205673218},{"id":"https://openalex.org/C2776459999","wikidata":"https://www.wikidata.org/wiki/Q2119376","display_name":"Fidelity","level":2,"score":0.6545581817626953},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.6412997245788574},{"id":"https://openalex.org/C106131492","wikidata":"https://www.wikidata.org/wiki/Q3072260","display_name":"Filter (signal processing)","level":2,"score":0.5976459383964539},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5855918526649475},{"id":"https://openalex.org/C106189395","wikidata":"https://www.wikidata.org/wiki/Q176789","display_name":"Markov decision process","level":3,"score":0.5773203372955322},{"id":"https://openalex.org/C2780801425","wikidata":"https://www.wikidata.org/wiki/Q5164392","display_name":"Construct (python library)","level":2,"score":0.5592030882835388},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.5483397841453552},{"id":"https://openalex.org/C74193536","wikidata":"https://www.wikidata.org/wiki/Q574844","display_name":"Kernel (algebra)","level":2,"score":0.5395329594612122},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5163391828536987},{"id":"https://openalex.org/C97541855","wikidata":"https://www.wikidata.org/wiki/Q830687","display_name":"Reinforcement learning","level":2,"score":0.46252140402793884},{"id":"https://openalex.org/C165464430","wikidata":"https://www.wikidata.org/wiki/Q1570441","display_name":"Parameterized complexity","level":2,"score":0.42757105827331543},{"id":"https://openalex.org/C159886148","wikidata":"https://www.wikidata.org/wiki/Q176645","display_name":"Markov process","level":2,"score":0.3674992620944977},{"id":"https://openalex.org/C98763669","wikidata":"https://www.wikidata.org/wiki/Q176645","display_name":"Markov chain","level":2,"score":0.3056056797504425},{"id":"https://openalex.org/C163836022","wikidata":"https://www.wikidata.org/wiki/Q6771326","display_name":"Markov model","level":3,"score":0.24523749947547913},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.13326379656791687},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.10744449496269226},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.0},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"score":0.0},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.0},{"id":"https://openalex.org/C187736073","wikidata":"https://www.wikidata.org/wiki/Q2920921","display_name":"Management","level":1,"score":0.0},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/iv55152.2023.10186722","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/iv55152.2023.10186722","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 IEEE Intelligent Vehicles Symposium (IV)","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":0.7200000286102295}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":29,"referenced_works":["https://openalex.org/W1657674574","https://openalex.org/W2110292307","https://openalex.org/W2141559023","https://openalex.org/W2156371714","https://openalex.org/W2168359464","https://openalex.org/W2169294731","https://openalex.org/W2333874039","https://openalex.org/W2739957299","https://openalex.org/W2905249540","https://openalex.org/W2910453440","https://openalex.org/W2947751203","https://openalex.org/W2963412383","https://openalex.org/W2963946410","https://openalex.org/W2996795455","https://openalex.org/W3021796787","https://openalex.org/W3041133507","https://openalex.org/W3148740559","https://openalex.org/W3209562871","https://openalex.org/W4211121497","https://openalex.org/W4285307725","https://openalex.org/W4295719664","https://openalex.org/W4297744728","https://openalex.org/W4319988532","https://openalex.org/W6636922475","https://openalex.org/W6680962669","https://openalex.org/W6683176904","https://openalex.org/W6738637145","https://openalex.org/W6741977017","https://openalex.org/W6745935785"],"related_works":["https://openalex.org/W2096013579","https://openalex.org/W52153049","https://openalex.org/W1760611253","https://openalex.org/W1589140671","https://openalex.org/W1515117609","https://openalex.org/W2049472152","https://openalex.org/W4323315247","https://openalex.org/W2294884454","https://openalex.org/W3169161914","https://openalex.org/W4321379664"],"abstract_inverted_index":{"One":[0],"of":[1,4,13,60,124,136,146],"the":[2,11,38,46,194,199,203,212],"bottlenecks":[3],"training":[5,14],"autonomous":[6,98],"vehicle":[7,99],"(AV)":[8],"agents":[9],"is":[10,23,109],"variability":[12],"environments.":[15,75,156],"Since":[16],"learning":[17],"optimal":[18],"policies":[19,59,83,126,145,152,185,197],"for":[20,84,127,186],"unseen":[21,66,155],"environments":[22,88,149,189,216],"often":[24],"very":[25],"costly":[26],"and":[27,139,166,180,220],"requires":[28],"substantial":[29],"data":[30,205],"collection,":[31],"it":[32],"becomes":[33],"computationally":[34],"intractable":[35],"to":[36,56,63,65,73,81,150,153,183],"train":[37],"agent":[39],"on":[40,96,161],"every":[41],"possible":[42],"environment":[43],"or":[44,87,188],"task":[45],"AV":[47,165],"may":[48],"encounter.This":[49],"paper":[50],"introduces":[51],"a":[52,112,134,167,177],"zero-shot":[53],"filtering":[54],"approach":[55],"interpolate":[57],"learned":[58,90,125,201],"past":[61,208],"experiences":[62],"generalize":[64],"ones.":[67],"We":[68,92,119,157],"use":[69],"an":[70,97,163],"experience":[71,174],"kernel":[72],"correlate":[74],"These":[76],"correlations":[77],"are":[78],"then":[79],"exploited":[80,219],"produce":[82],"new":[85,196],"tasks":[86,187],"from":[89,207],"policies.":[91],"demonstrate":[93,158],"our":[94,159,173],"methods":[95],"driving":[100],"through":[101],"T-intersections":[102],"with":[103,129],"different":[104,215],"characteristics,":[105],"where":[106],"its":[107],"behavior":[108],"modeled":[110],"as":[111],"partially":[113],"observable":[114],"Markov":[115],"decision":[116],"process":[117],"(POMDP).":[118],"first":[120],"construct":[121],"compact":[122],"representations":[123],"POMDPs":[128],"unknown":[130],"transition":[131],"functions":[132],"given":[133],"dataset":[135],"sequential":[137],"actions":[138],"observations.":[140],"Then,":[141],"we":[142],"filter":[143,175],"parameterized":[144],"previously":[147],"visited":[148],"generate":[151],"new,":[154],"approaches":[160],"both":[162],"actual":[164],"high-fidelity":[168],"simulator.":[169],"Results":[170],"indicate":[171],"that":[172,211],"offers":[176],"fast,":[178],"low-effort,":[179],"near-optimal":[181],"solution":[182],"create":[184],"never":[190],"seen":[191],"before.":[192],"Furthermore,":[193],"generated":[195],"outperform":[198],"policy":[200],"using":[202],"entire":[204],"collected":[206],"environments,":[209],"suggesting":[210],"correlation":[213],"among":[214],"can":[217,223],"be":[218,224],"irrelevant":[221],"ones":[222],"filtered":[225],"out.":[226]},"counts_by_year":[],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}
