{"id":"https://openalex.org/W4296405226","doi":"https://doi.org/10.48550/arxiv.2209.07550","title":"Human-level Atari 200x faster","display_name":"Human-level Atari 200x faster","publication_year":2022,"publication_date":"2022-09-15","ids":{"openalex":"https://openalex.org/W4296405226","doi":"https://doi.org/10.48550/arxiv.2209.07550"},"language":"en","primary_location":{"id":"pmh:oai:arXiv.org:2209.07550","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2209.07550","pdf_url":"https://arxiv.org/pdf/2209.07550","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"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":"","raw_type":"text"},"type":"preprint","indexed_in":["arxiv","datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2209.07550","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5060324637","display_name":"Steven Kapturowski","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Kapturowski, Steven","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5062691145","display_name":"V\u00edctor Campos","orcid":"https://orcid.org/0000-0002-2730-4640"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Campos, V\u00edctor","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5112495623","display_name":"Ray Jiang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Jiang, Ray","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5017568280","display_name":"Nemanja Rakicevic","orcid":"https://orcid.org/0000-0003-3323-2193"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Raki\u0107evi\u0107, Nemanja","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5033135596","display_name":"Hado van Hasselt","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"van Hasselt, Hado","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5030688126","display_name":"Charles D. Blundell","orcid":"https://orcid.org/0000-0002-1439-9126"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Blundell, Charles","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5016838762","display_name":"Adri\u00e0 Puigdom\u00e8nech Badia","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Badia, Adri\u00e0 Puigdom\u00e8nech","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":false,"cited_by_count":6,"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":0.9969000220298767,"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":0.9969000220298767,"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/T12761","display_name":"Data Stream Mining Techniques","score":0.988099992275238,"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/T12026","display_name":"Explainable Artificial Intelligence (XAI)","score":0.97079998254776,"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/computer-science","display_name":"Computer science","score":0.7621257901191711},{"id":"https://openalex.org/keywords/leverage","display_name":"Leverage (statistics)","score":0.7228723764419556},{"id":"https://openalex.org/keywords/normalization","display_name":"Normalization (sociology)","score":0.5354528427124023},{"id":"https://openalex.org/keywords/reinforcement-learning","display_name":"Reinforcement learning","score":0.5330371260643005},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.5051794648170471},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.46828576922416687},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4568856358528137},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4439907371997833},{"id":"https://openalex.org/keywords/baseline","display_name":"Baseline (sea)","score":0.4271976351737976}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7621257901191711},{"id":"https://openalex.org/C153083717","wikidata":"https://www.wikidata.org/wiki/Q6535263","display_name":"Leverage (statistics)","level":2,"score":0.7228723764419556},{"id":"https://openalex.org/C136886441","wikidata":"https://www.wikidata.org/wiki/Q926129","display_name":"Normalization (sociology)","level":2,"score":0.5354528427124023},{"id":"https://openalex.org/C97541855","wikidata":"https://www.wikidata.org/wiki/Q830687","display_name":"Reinforcement learning","level":2,"score":0.5330371260643005},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.5051794648170471},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.46828576922416687},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4568856358528137},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4439907371997833},{"id":"https://openalex.org/C12725497","wikidata":"https://www.wikidata.org/wiki/Q810247","display_name":"Baseline (sea)","level":2,"score":0.4271976351737976},{"id":"https://openalex.org/C111368507","wikidata":"https://www.wikidata.org/wiki/Q43518","display_name":"Oceanography","level":1,"score":0.0},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"id":"https://openalex.org/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","level":1,"score":0.0},{"id":"https://openalex.org/C19165224","wikidata":"https://www.wikidata.org/wiki/Q23404","display_name":"Anthropology","level":1,"score":0.0},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.0},{"id":"https://openalex.org/C127313418","wikidata":"https://www.wikidata.org/wiki/Q1069","display_name":"Geology","level":0,"score":0.0},{"id":"https://openalex.org/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"score":0.0},{"id":"https://openalex.org/C13280743","wikidata":"https://www.wikidata.org/wiki/Q131089","display_name":"Geodesy","level":1,"score":0.0},{"id":"https://openalex.org/C144024400","wikidata":"https://www.wikidata.org/wiki/Q21201","display_name":"Sociology","level":0,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"pmh:oai:arXiv.org:2209.07550","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2209.07550","pdf_url":"https://arxiv.org/pdf/2209.07550","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"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":"","raw_type":"text"},{"id":"doi:10.48550/arxiv.2209.07550","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2209.07550","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_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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"Preprint"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:2209.07550","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2209.07550","pdf_url":"https://arxiv.org/pdf/2209.07550","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"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":"","raw_type":"text"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":["https://openalex.org/W2378211422","https://openalex.org/W2383111961","https://openalex.org/W2365952365","https://openalex.org/W2352448290","https://openalex.org/W2380820513","https://openalex.org/W2913146933","https://openalex.org/W2745001401","https://openalex.org/W4321353415","https://openalex.org/W2372385138","https://openalex.org/W2768698792"],"abstract_inverted_index":{"The":[0,26,157],"task":[1],"of":[2,13,31,33,37,50,78,86,101,108,121,195,202],"building":[3],"general":[4],"agents":[5],"that":[6],"perform":[7,113],"well":[8],"over":[9,46],"a":[10,34,93,98,105,119,138,180,193,199,226],"wide":[11,48,200],"range":[12,49,120,201],"tasks":[14],"has":[15,28],"been":[16,29],"an":[17,166,205],"important":[18],"goal":[19],"in":[20,53,212],"reinforcement":[21],"learning":[22,192],"since":[23],"its":[24],"inception.":[25],"problem":[27],"subject":[30],"research":[32],"large":[35],"body":[36],"work,":[38],"with":[39,149,198],"performance":[40,148],"frequently":[41],"measured":[42],"by":[43],"observing":[44],"scores":[45],"the":[47,54,60,65,76,114,129,176,184,219,235],"environments":[51],"contained":[52],"Atari":[55],"57":[56,70],"benchmark.":[57],"Agent57":[58,91],"was":[59],"first":[61],"agent":[62],"to":[63,88,103,111,136,161,214,232],"surpass":[64],"human":[66,115],"benchmark":[67],"on":[68],"all":[69],"games,":[71],"but":[72],"this":[73],"came":[74],"at":[75],"cost":[77],"poor":[79],"data-efficiency,":[80],"requiring":[81],"nearly":[82],"80":[83],"billion":[84],"frames":[85],"experience":[87,109],"achieve.":[89],"Taking":[90],"as":[92,153],"starting":[94],"point,":[95],"we":[96,125],"employ":[97],"diverse":[99],"set":[100,194],"strategies":[102],"achieve":[104],"200-fold":[106],"reduction":[107],"needed":[110],"out":[112,234],"baseline.":[116],"We":[117,144],"investigate":[118],"instabilities":[122],"and":[123,132,141,155,186,224],"bottlenecks":[124],"encountered":[126],"while":[127],"reducing":[128],"data":[130],"regime,":[131],"propose":[133],"effective":[134],"solutions":[135],"build":[137],"more":[139],"robust":[140],"efficient":[142],"agent.":[143],"also":[145],"demonstrate":[146],"competitive":[147],"high-performing":[150],"methods":[151],"such":[152],"Muesli":[154],"MuZero.":[156],"four":[158],"key":[159],"components":[160],"our":[162],"approach":[163],"are":[164],"(1)":[165],"approximate":[167],"trust":[168],"region":[169],"method":[170,229],"which":[171,188,230],"enables":[172],"stable":[173],"bootstrapping":[174],"from":[175,210],"online":[177],"network,":[178],"(2)":[179],"normalisation":[181],"scheme":[182],"for":[183,221],"loss":[185],"priorities":[187],"improves":[189],"robustness":[190],"when":[191],"value":[196],"functions":[197],"scales,":[203],"(3)":[204],"improved":[206],"architecture":[207],"employing":[208],"techniques":[209],"NFNets":[211],"order":[213],"leverage":[215],"deeper":[216],"networks":[217],"without":[218],"need":[220],"normalization":[222],"layers,":[223],"(4)":[225],"policy":[227,238],"distillation":[228],"serves":[231],"smooth":[233],"instantaneous":[236],"greedy":[237],"overtime.":[239]},"counts_by_year":[{"year":2024,"cited_by_count":3},{"year":2023,"cited_by_count":3}],"updated_date":"2026-07-01T06:00:48.157686","created_date":"2025-10-10T00:00:00"}
