{"id":"https://openalex.org/W4303644981","doi":"https://doi.org/10.1007/s10846-022-01747-5","title":"High Performance on Atari Games Using Perceptual Control Architecture Without Training","display_name":"High Performance on Atari Games Using Perceptual Control Architecture Without Training","publication_year":2022,"publication_date":"2022-10-01","ids":{"openalex":"https://openalex.org/W4303644981","doi":"https://doi.org/10.1007/s10846-022-01747-5"},"language":"en","primary_location":{"id":"doi:10.1007/s10846-022-01747-5","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s10846-022-01747-5","pdf_url":"https://link.springer.com/content/pdf/10.1007/s10846-022-01747-5.pdf","source":{"id":"https://openalex.org/S91329792","display_name":"Journal of Intelligent & Robotic Systems","issn_l":"0921-0296","issn":["0921-0296","1573-0409"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of Intelligent &amp; Robotic Systems","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"hybrid","oa_url":"https://link.springer.com/content/pdf/10.1007/s10846-022-01747-5.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5002216636","display_name":"Tauseef Gulrez","orcid":"https://orcid.org/0000-0003-1468-2797"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Tauseef Gulrez","raw_affiliation_strings":["Department of Computing and Research, Syscon Pty. Ltd., Vanguard Cr., Point Cook, Melbourne, 3030, VIC, Australia"],"affiliations":[{"raw_affiliation_string":"Department of Computing and Research, Syscon Pty. Ltd., Vanguard Cr., Point Cook, Melbourne, 3030, VIC, Australia","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5042961189","display_name":"Warren Mansell","orcid":"https://orcid.org/0000-0002-5697-1784"},"institutions":[{"id":"https://openalex.org/I205640436","display_name":"Curtin University","ror":"https://ror.org/02n415q13","country_code":"AU","type":"education","lineage":["https://openalex.org/I205640436"]}],"countries":["AU"],"is_corresponding":true,"raw_author_name":"Warren Mansell","raw_affiliation_strings":["School of Population Health, Faculty of Health Sciences, Curtin University, Perth, 6102, WA, Australia"],"affiliations":[{"raw_affiliation_string":"School of Population Health, Faculty of Health Sciences, Curtin University, Perth, 6102, WA, Australia","institution_ids":["https://openalex.org/I205640436"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5042961189"],"corresponding_institution_ids":["https://openalex.org/I205640436"],"apc_list":{"value":2390,"currency":"EUR","value_usd":2990},"apc_paid":{"value":2390,"currency":"EUR","value_usd":2990},"fwci":1.104,"has_fulltext":true,"cited_by_count":9,"citation_normalized_percentile":{"value":0.81589622,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":96,"max":99},"biblio":{"volume":"106","issue":"2","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":0.9983000159263611,"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":0.9983000159263611,"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/T11674","display_name":"Sports Analytics and Performance","score":0.9648000001907349,"subfield":{"id":"https://openalex.org/subfields/2002","display_name":"Economics and Econometrics"},"field":{"id":"https://openalex.org/fields/20","display_name":"Economics, Econometrics and Finance"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T11975","display_name":"Evolutionary Algorithms and Applications","score":0.9610999822616577,"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":0.7815566658973694},{"id":"https://openalex.org/keywords/perception","display_name":"Perception","score":0.7157937288284302},{"id":"https://openalex.org/keywords/signal","display_name":"SIGNAL (programming language)","score":0.5970897078514099},{"id":"https://openalex.org/keywords/reinforcement-learning","display_name":"Reinforcement learning","score":0.5789815187454224},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.48980236053466797},{"id":"https://openalex.org/keywords/simple","display_name":"Simple (philosophy)","score":0.4799099862575531},{"id":"https://openalex.org/keywords/control","display_name":"Control (management)","score":0.473716676235199},{"id":"https://openalex.org/keywords/training","display_name":"Training (meteorology)","score":0.45584481954574585},{"id":"https://openalex.org/keywords/breakout","display_name":"Breakout","score":0.44527652859687805},{"id":"https://openalex.org/keywords/architecture","display_name":"Architecture","score":0.42946815490722656},{"id":"https://openalex.org/keywords/video-game","display_name":"Video game","score":0.4249873161315918},{"id":"https://openalex.org/keywords/construct","display_name":"Construct (python library)","score":0.4223254919052124},{"id":"https://openalex.org/keywords/human\u2013computer-interaction","display_name":"Human\u2013computer interaction","score":0.34376394748687744},{"id":"https://openalex.org/keywords/multimedia","display_name":"Multimedia","score":0.16176143288612366},{"id":"https://openalex.org/keywords/psychology","display_name":"Psychology","score":0.11152994632720947}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7815566658973694},{"id":"https://openalex.org/C26760741","wikidata":"https://www.wikidata.org/wiki/Q160402","display_name":"Perception","level":2,"score":0.7157937288284302},{"id":"https://openalex.org/C2779843651","wikidata":"https://www.wikidata.org/wiki/Q7390335","display_name":"SIGNAL (programming language)","level":2,"score":0.5970897078514099},{"id":"https://openalex.org/C97541855","wikidata":"https://www.wikidata.org/wiki/Q830687","display_name":"Reinforcement learning","level":2,"score":0.5789815187454224},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.48980236053466797},{"id":"https://openalex.org/C2780586882","wikidata":"https://www.wikidata.org/wiki/Q7520643","display_name":"Simple (philosophy)","level":2,"score":0.4799099862575531},{"id":"https://openalex.org/C2775924081","wikidata":"https://www.wikidata.org/wiki/Q55608371","display_name":"Control (management)","level":2,"score":0.473716676235199},{"id":"https://openalex.org/C2777211547","wikidata":"https://www.wikidata.org/wiki/Q17141490","display_name":"Training (meteorology)","level":2,"score":0.45584481954574585},{"id":"https://openalex.org/C2778091849","wikidata":"https://www.wikidata.org/wiki/Q4959649","display_name":"Breakout","level":2,"score":0.44527652859687805},{"id":"https://openalex.org/C123657996","wikidata":"https://www.wikidata.org/wiki/Q12271","display_name":"Architecture","level":2,"score":0.42946815490722656},{"id":"https://openalex.org/C3018412434","wikidata":"https://www.wikidata.org/wiki/Q7889","display_name":"Video game","level":2,"score":0.4249873161315918},{"id":"https://openalex.org/C2780801425","wikidata":"https://www.wikidata.org/wiki/Q5164392","display_name":"Construct (python library)","level":2,"score":0.4223254919052124},{"id":"https://openalex.org/C107457646","wikidata":"https://www.wikidata.org/wiki/Q207434","display_name":"Human\u2013computer interaction","level":1,"score":0.34376394748687744},{"id":"https://openalex.org/C49774154","wikidata":"https://www.wikidata.org/wiki/Q131765","display_name":"Multimedia","level":1,"score":0.16176143288612366},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.11152994632720947},{"id":"https://openalex.org/C153294291","wikidata":"https://www.wikidata.org/wiki/Q25261","display_name":"Meteorology","level":1,"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/C142362112","wikidata":"https://www.wikidata.org/wiki/Q735","display_name":"Art","level":0,"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/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C10138342","wikidata":"https://www.wikidata.org/wiki/Q43015","display_name":"Finance","level":1,"score":0.0},{"id":"https://openalex.org/C169760540","wikidata":"https://www.wikidata.org/wiki/Q207011","display_name":"Neuroscience","level":1,"score":0.0},{"id":"https://openalex.org/C111472728","wikidata":"https://www.wikidata.org/wiki/Q9471","display_name":"Epistemology","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/C153349607","wikidata":"https://www.wikidata.org/wiki/Q36649","display_name":"Visual arts","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1007/s10846-022-01747-5","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s10846-022-01747-5","pdf_url":"https://link.springer.com/content/pdf/10.1007/s10846-022-01747-5.pdf","source":{"id":"https://openalex.org/S91329792","display_name":"Journal of Intelligent & Robotic Systems","issn_l":"0921-0296","issn":["0921-0296","1573-0409"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of Intelligent &amp; Robotic Systems","raw_type":"journal-article"},{"id":"pmh:oai:pure.atira.dk:openaire/8c8d8ebe-9127-479e-a9e9-573b77afec46","is_oa":true,"landing_page_url":"https://research.manchester.ac.uk/en/publications/8c8d8ebe-9127-479e-a9e9-573b77afec46","pdf_url":null,"source":{"id":"https://openalex.org/S4306400662","display_name":"Research Explorer (The University of Manchester)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I28407311","host_organization_name":"University of Manchester","host_organization_lineage":["https://openalex.org/I28407311"],"host_organization_lineage_names":[],"type":"repository"},"license":"other-oa","license_id":"https://openalex.org/licenses/other-oa","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Gulrez, T & Mansell, W 2022, 'High Performance on Atari Games Using Perceptual Control Architecture Without Training', Journal of Intelligent & Robotic Systems. https://doi.org/10.1007/s10846-022-01747-5","raw_type":"info:eu-repo/semantics/publishedVersion"}],"best_oa_location":{"id":"doi:10.1007/s10846-022-01747-5","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s10846-022-01747-5","pdf_url":"https://link.springer.com/content/pdf/10.1007/s10846-022-01747-5.pdf","source":{"id":"https://openalex.org/S91329792","display_name":"Journal of Intelligent & Robotic Systems","issn_l":"0921-0296","issn":["0921-0296","1573-0409"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of Intelligent &amp; Robotic Systems","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4303644981.pdf","grobid_xml":"https://content.openalex.org/works/W4303644981.grobid-xml"},"referenced_works_count":27,"referenced_works":["https://openalex.org/W2074223061","https://openalex.org/W2118688707","https://openalex.org/W2144102937","https://openalex.org/W2145339207","https://openalex.org/W2153590782","https://openalex.org/W2173564293","https://openalex.org/W2198041288","https://openalex.org/W2208548157","https://openalex.org/W2260756217","https://openalex.org/W2614353852","https://openalex.org/W2746553466","https://openalex.org/W2746753258","https://openalex.org/W2761873684","https://openalex.org/W2765302304","https://openalex.org/W2962872206","https://openalex.org/W2963430173","https://openalex.org/W2989847975","https://openalex.org/W3000547322","https://openalex.org/W3008067022","https://openalex.org/W3021290928","https://openalex.org/W3029977317","https://openalex.org/W3031637535","https://openalex.org/W3118210634","https://openalex.org/W3176707157","https://openalex.org/W3187516880","https://openalex.org/W4210359207","https://openalex.org/W6775522024"],"related_works":["https://openalex.org/W3074294383","https://openalex.org/W2186405473","https://openalex.org/W4206669594","https://openalex.org/W2959276766","https://openalex.org/W4295941380","https://openalex.org/W260766989","https://openalex.org/W3139193008","https://openalex.org/W4247927622","https://openalex.org/W2371587969","https://openalex.org/W3111983280"],"abstract_inverted_index":{"Abstract":[0],"Deep":[1],"reinforcement":[2],"learning":[3,173],"(DRL)":[4],"requires":[5,57],"large":[6],"samples":[7,60],"and":[8,61,90,130,143],"a":[9,52,65,93,107,169],"long":[10,20],"training":[11,23,59,62],"time":[12,63],"to":[13,24,50,79,110,114,133,145,179],"operate":[14],"optimally.":[15],"Yet":[16],"humans":[17],"rarely":[18],"require":[19],"periods":[21],"of":[22,42,172],"perform":[25,161],"well":[26,162],"on":[27,157],"novel":[28],"tasks,":[29],"such":[30],"as":[31,138,140],"computer":[32],"games,":[33],"once":[34],"they":[35],"are":[36],"provided":[37],"with":[38],"an":[39],"accurate":[40],"program":[41],"instructions.":[43],"We":[44,118,165],"used":[45],"perceptual":[46,88,104,153],"control":[47,154],"theory":[48],"(PCT)":[49],"construct":[51],"simple":[53,158],"closed-loop":[54],"model":[55,76,122],"which":[56],"no":[58],"within":[64],"video":[66],"game":[67],"study":[68,150],"using":[69],"the":[70,83,99,120],"Arcade":[71],"Learning":[72],"Environment":[73],"(ALE).":[74],"The":[75],"was":[77],"programmed":[78],"parse":[80],"inputs":[81],"from":[82,106],"environment":[84],"into":[85],"hierarchically":[86],"organised":[87],"signals,":[89],"it":[91],"computed":[92],"dynamic":[94],"error":[95],"signal":[96,101,109],"by":[97,167],"subtracting":[98],"incoming":[100],"for":[102],"each":[103],"variable":[105],"reference":[108],"drive":[111],"output":[112],"signals":[113],"reduce":[115],"this":[116],"error.":[117],"tested":[119],"same":[121],"across":[123],"three":[124],"different":[125],"Atari":[126],"games":[127],"Breakout,":[128],"Pong":[129],"Video":[131],"Pinball":[132],"achieve":[134],"performance":[135],"at":[136],"least":[137],"high":[139],"DRL":[141],"paradigms,":[142],"close":[144],"good":[146],"human":[147],"performance.":[148],"Our":[149],"shows":[151],"that":[152,174],"models,":[155],"based":[156],"assumptions,":[159],"can":[160],"without":[163],"learning.":[164],"conclude":[166],"specifying":[168],"parsimonious":[170],"role":[171],"may":[175],"be":[176],"more":[177],"similar":[178],"psychological":[180],"functioning.":[181]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":3},{"year":2024,"cited_by_count":5}],"updated_date":"2026-03-20T23:20:44.827607","created_date":"2025-10-10T00:00:00"}
