乐胖代购免代理版

{"id":"https://openalex.org/W4377299725","doi":"https://doi.org/10.48550/arxiv.2305.11290","title":"Massively Scalable Inverse Reinforcement Learning in Google Maps","display_name":"Massively Scalable Inverse Reinforcement Learning in Google Maps","publication_year":2023,"publication_date":"2023-01-01","ids":{"openalex":"https://openalex.org/W4377299725","doi":"https://doi.org/10.48550/arxiv.2305.11290"},"language":"en","primary_location":{"is_oa":true,"landing_page_url":"https://arxiv.org/abs/2305.11290","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_indexed_in_scopus":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":["Cornell University"],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false},"type":"preprint","type_crossref":"posted-content","indexed_in":["arxiv","datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/abs/2305.11290","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5065802911","display_name":"Matt Barnes","orcid":"https://orcid.org/0000-0002-0702-5222"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Barnes, Matt","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5087147853","display_name":"Matthew Abueg","orcid":"https://orcid.org/0000-0002-4848-1988"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Abueg, Matthew","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5111863919","display_name":"Oliver F. Lange","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Lange, Oliver F.","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5074486494","display_name":"Matt Deeds","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Deeds, Matt","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5028570776","display_name":"Jason M. Trader","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Trader, Jason","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5006464145","display_name":"Denali Molitor","orcid":"https://orcid.org/0000-0001-9750-3533"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Molitor, Denali","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5002747297","display_name":"Markus Wulfmeier","orcid":"https://orcid.org/0000-0003-1802-4492"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wulfmeier, Markus","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5038978854","display_name":"Shawn O\u2019Banion","orcid":"https://orcid.org/0000-0003-3950-6474"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"O'Banion, Shawn","raw_affiliation_strings":[],"affiliations":[]}],"institution_assertions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.0,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":0,"max":67},"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"primary_topic":{"id":"https://openalex.org/T11106","display_name":"Data Management and Algorithms","score":0.9668,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"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/T11106","display_name":"Data Management and Algorithms","score":0.9668,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7478057},{"id":"https://openalex.org/C97541855","wikidata":"https://www.wikidata.org/wiki/Q830687","display_name":"Reinforcement learning","level":2,"score":0.74233055},{"id":"https://openalex.org/C48044578","wikidata":"https://www.wikidata.org/wiki/Q727490","display_name":"Scalability","level":2,"score":0.6742533},{"id":"https://openalex.org/C190475519","wikidata":"https://www.wikidata.org/wiki/Q544384","display_name":"Massively parallel","level":2,"score":0.616395},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.5330198},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.5129904},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.41783208},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.41320938},{"id":"https://openalex.org/C106189395","wikidata":"https://www.wikidata.org/wiki/Q176789","display_name":"Markov decision process","level":3,"score":0.41177413},{"id":"https://openalex.org/C120314980","wikidata":"https://www.wikidata.org/wiki/Q180634","display_name":"Distributed computing","level":1,"score":0.33770037},{"id":"https://openalex.org/C159886148","wikidata":"https://www.wikidata.org/wiki/Q176645","display_name":"Markov process","level":2,"score":0.14045396},{"id":"https://openalex.org/C173608175","wikidata":"https://www.wikidata.org/wiki/Q232661","display_name":"Parallel computing","level":1,"score":0.112106234},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.09368509},{"id":"https://openalex.org/C77088390","wikidata":"https://www.wikidata.org/wiki/Q8513","display_name":"Database","level":1,"score":0.0},{"id":"https://openalex.org/C151730666","wikidata":"https://www.wikidata.org/wiki/Q7205","display_name":"Paleontology","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},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"is_oa":true,"landing_page_url":"https://arxiv.org/abs/2305.11290","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_indexed_in_scopus":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":["Cornell University"],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false},{"is_oa":false,"landing_page_url":"https://api.datacite.org/dois/10.48550/arxiv.2305.11290","pdf_url":null,"source":{"id":"https://openalex.org/S4393179698","display_name":"DataCite API","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_indexed_in_scopus":false,"is_core":false,"host_organization":"https://openalex.org/I4210145204","host_organization_name":"DataCite","host_organization_lineage":["https://openalex.org/I4210145204"],"host_organization_lineage_names":["DataCite"],"type":"metadata"},"license":null,"license_id":null,"version":null}],"best_oa_location":{"is_oa":true,"landing_page_url":"https://arxiv.org/abs/2305.11290","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_indexed_in_scopus":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":["Cornell University"],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false},"sustainable_development_goals":[{"score":0.54,"id":"https://metadata.un.org/sdg/9","display_name":"Industry, innovation and infrastructure"}],"grants":[],"datasets":[],"versions":[],"referenced_works_count":0,"referenced_works":[],"related_works":["https://openalex.org/W3168977894","https://openalex.org/W3096874164","https://openalex.org/W2937181779","https://openalex.org/W2386410636","https://openalex.org/W2357975469","https://openalex.org/W2341346307","https://openalex.org/W2182304831","https://openalex.org/W2145363145","https://openalex.org/W1985560493","https://openalex.org/W1626977535"],"abstract_inverted_index":{"Inverse":[0,98],"reinforcement":[1],"learning":[2,11],"(IRL)":[3],"offers":[4],"a":[5,54,76,101,123,127,134,153],"powerful":[6],"and":[7,32,48,68,85,137,175],"general":[8],"framework":[9],"for":[10],"humans'":[12],"latent":[13],"preferences":[14],"in":[15,64,95,122,130,152],"route":[16,131],"recommendation,":[17],"yet":[18,87],"no":[19],"approach":[20],"has":[21],"successfully":[22],"addressed":[23],"planetary-scale":[24],"problems":[25],"with":[26],"hundreds":[27],"of":[28,30,81,104,141,149,165],"millions":[29],"states":[31],"demonstration":[33],"trajectories.":[34],"In":[35],"this":[36],"paper,":[37],"we":[38],"introduce":[39],"scaling":[40],"techniques":[41],"based":[42],"on":[43],"graph":[44],"compression,":[45],"spatial":[46],"parallelization,":[47],"improved":[49],"initialization":[50],"conditions":[51],"inspired":[52],"by":[53,160],"connection":[55],"to":[56,138,156,178],"eigenvector":[57],"algorithms.":[58],"We":[59,158],"revisit":[60],"classic":[61,105],"IRL":[62,106,150],"methods":[63],"the":[65,70,79,139,145],"routing":[66],"context,":[67],"make":[69],"key":[71,166],"observation":[72],"that":[73,108,125],"there":[74],"exists":[75],"trade-off":[77],"between":[78],"use":[80],"cheap,":[82],"deterministic":[83],"planners":[84],"expensive":[86],"robust":[88],"stochastic":[89],"policies.":[90],"This":[91],"insight":[92],"is":[93],"leveraged":[94],"Receding":[96],"Horizon":[97],"Planning":[99],"(RHIP),":[100],"new":[102],"generalization":[103],"algorithms":[107,151],"provides":[109],"fine-grained":[110],"control":[111],"over":[112],"performance":[113],"trade-offs":[114],"via":[115,182],"its":[116],"planning":[117],"horizon.":[118],"Our":[119],"contributions":[120],"culminate":[121],"policy":[124],"achieves":[126],"16-24%":[128],"improvement":[129],"quality":[132],"at":[133],"global":[135],"scale,":[136],"best":[140],"our":[142],"knowledge,":[143],"represents":[144],"largest":[146],"published":[147],"study":[148,164],"real-world":[154],"setting":[155],"date.":[157],"conclude":[159],"conducting":[161],"an":[162],"ablation":[163],"components,":[167],"presenting":[168],"negative":[169],"results":[170],"from":[171],"alternative":[172],"eigenvalue":[173],"solvers,":[174],"identifying":[176],"opportunities":[177],"further":[179],"improve":[180],"scalability":[181],"IRL-specific":[183],"batching":[184],"strategies.":[185]},"cited_by_api_url":"https://api.openalex.org/works?filter=cites:W4377299725","counts_by_year":[],"updated_date":"2025-01-21T07:01:47.680506","created_date":"2023-05-23"}