{"id":"https://openalex.org/W4300597967","doi":"https://doi.org/10.1145/3549179.3549181","title":"FPGA hardware implementation of Q-learning algorithm with low resource consumption","display_name":"FPGA hardware implementation of Q-learning algorithm with low resource consumption","publication_year":2022,"publication_date":"2022-07-29","ids":{"openalex":"https://openalex.org/W4300597967","doi":"https://doi.org/10.1145/3549179.3549181"},"language":"en","primary_location":{"id":"doi:10.1145/3549179.3549181","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3549179.3549181","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2022 4th International Conference on Pattern Recognition and Intelligent Systems","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/A5021656478","display_name":"XIAOJUAN LIU","orcid":null},"institutions":[{"id":"https://openalex.org/I170215575","display_name":"National University of Defense Technology","ror":"https://ror.org/05d2yfz11","country_code":"CN","type":"education","lineage":["https://openalex.org/I170215575"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"XIAOJUAN LIU","raw_affiliation_strings":["College of Electronic Science and Engineering, National University of Defense Technology, China"],"affiliations":[{"raw_affiliation_string":"College of Electronic Science and Engineering, National University of Defense Technology, China","institution_ids":["https://openalex.org/I170215575"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5052187070","display_name":"Jietao Diao","orcid":null},"institutions":[{"id":"https://openalex.org/I170215575","display_name":"National University of Defense Technology","ror":"https://ror.org/05d2yfz11","country_code":"CN","type":"education","lineage":["https://openalex.org/I170215575"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"JIETAO DIAO","raw_affiliation_strings":["College of Electronic Science and Engineering, National University of Defense Technology, China"],"affiliations":[{"raw_affiliation_string":"College of Electronic Science and Engineering, National University of Defense Technology, China","institution_ids":["https://openalex.org/I170215575"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5055687914","display_name":"NAN LI","orcid":null},"institutions":[{"id":"https://openalex.org/I170215575","display_name":"National University of Defense Technology","ror":"https://ror.org/05d2yfz11","country_code":"CN","type":"education","lineage":["https://openalex.org/I170215575"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"NAN LI","raw_affiliation_strings":["College of Electronic Science and Engineering, National University of Defense Technology, China"],"affiliations":[{"raw_affiliation_string":"College of Electronic Science and Engineering, National University of Defense Technology, China","institution_ids":["https://openalex.org/I170215575"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5021656478"],"corresponding_institution_ids":["https://openalex.org/I170215575"],"apc_list":null,"apc_paid":null,"fwci":0.0915,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.40683207,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":94},"biblio":{"volume":null,"issue":null,"first_page":"8","last_page":"13"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11992","display_name":"CCD and CMOS Imaging Sensors","score":0.9663000106811523,"subfield":{"id":"https://openalex.org/subfields/2208","display_name":"Electrical and Electronic Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T11992","display_name":"CCD and CMOS Imaging Sensors","score":0.9663000106811523,"subfield":{"id":"https://openalex.org/subfields/2208","display_name":"Electrical and Electronic 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/field-programmable-gate-array","display_name":"Field-programmable gate array","score":0.8139464855194092},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7768574357032776},{"id":"https://openalex.org/keywords/reinforcement-learning","display_name":"Reinforcement learning","score":0.5923025608062744},{"id":"https://openalex.org/keywords/architecture","display_name":"Architecture","score":0.5664507150650024},{"id":"https://openalex.org/keywords/q-learning","display_name":"Q-learning","score":0.5029224753379822},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.4825934171676636},{"id":"https://openalex.org/keywords/acceleration","display_name":"Acceleration","score":0.41961175203323364},{"id":"https://openalex.org/keywords/computer-architecture","display_name":"Computer architecture","score":0.4104537069797516},{"id":"https://openalex.org/keywords/embedded-system","display_name":"Embedded system","score":0.4085378348827362},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.2722499370574951}],"concepts":[{"id":"https://openalex.org/C42935608","wikidata":"https://www.wikidata.org/wiki/Q190411","display_name":"Field-programmable gate array","level":2,"score":0.8139464855194092},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7768574357032776},{"id":"https://openalex.org/C97541855","wikidata":"https://www.wikidata.org/wiki/Q830687","display_name":"Reinforcement learning","level":2,"score":0.5923025608062744},{"id":"https://openalex.org/C123657996","wikidata":"https://www.wikidata.org/wiki/Q12271","display_name":"Architecture","level":2,"score":0.5664507150650024},{"id":"https://openalex.org/C188116033","wikidata":"https://www.wikidata.org/wiki/Q2664563","display_name":"Q-learning","level":3,"score":0.5029224753379822},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.4825934171676636},{"id":"https://openalex.org/C117896860","wikidata":"https://www.wikidata.org/wiki/Q11376","display_name":"Acceleration","level":2,"score":0.41961175203323364},{"id":"https://openalex.org/C118524514","wikidata":"https://www.wikidata.org/wiki/Q173212","display_name":"Computer architecture","level":1,"score":0.4104537069797516},{"id":"https://openalex.org/C149635348","wikidata":"https://www.wikidata.org/wiki/Q193040","display_name":"Embedded system","level":1,"score":0.4085378348827362},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.2722499370574951},{"id":"https://openalex.org/C74650414","wikidata":"https://www.wikidata.org/wiki/Q11397","display_name":"Classical mechanics","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/C153349607","wikidata":"https://www.wikidata.org/wiki/Q36649","display_name":"Visual arts","level":1,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3549179.3549181","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3549179.3549181","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2022 4th International Conference on Pattern Recognition and Intelligent Systems","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/8","score":0.5799999833106995,"display_name":"Decent work and economic growth"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":6,"referenced_works":["https://openalex.org/W2761694337","https://openalex.org/W2889068523","https://openalex.org/W2938157874","https://openalex.org/W3009478882","https://openalex.org/W3012383807","https://openalex.org/W3171049691"],"related_works":["https://openalex.org/W2742483371","https://openalex.org/W3096874164","https://openalex.org/W2166117066","https://openalex.org/W2357975469","https://openalex.org/W2136202932","https://openalex.org/W3087814763","https://openalex.org/W4376605461","https://openalex.org/W4400868993","https://openalex.org/W1967938402","https://openalex.org/W2361647908"],"abstract_inverted_index":{"Q-learning":[0,30,53,89],"is":[1,73,91],"a":[2,8,47,68],"kind":[3],"of":[4,11,88],"reinforcement":[5],"learning,":[6],"having":[7],"wide":[9],"range":[10],"applications":[12],"varying":[13],"in":[14,18,83],"different":[15],"fields.":[16],"However,":[17],"some":[19],"circumstances":[20],"like":[21],"robot":[22],"control":[23],"which":[24],"has":[25],"shorter":[26],"training":[27],"time":[28],"requirement,":[29],"algorithm":[31,54,90],"implemented":[32,56],"on":[33,59],"GPU":[34],"or":[35],"CPU":[36],"may":[37],"not":[38],"meet":[39],"the":[40,57,70,80,85],"requirement.":[41],"In":[42],"this":[43],"paper,":[44],"we":[45],"proposed":[46,82],"novel":[48],"serial":[49],"acceleration":[50],"architecture":[51,58,81],"for":[52],"and":[55],"xczu7ev-ffvc1156":[60],"FPGA":[61],"using":[62],"Vivado":[63],"2019.1":[64],"development":[65],"environment.":[66],"As":[67],"result,":[69],"resource":[71],"consumption":[72],"reduced":[74],"by":[75],"about":[76],"50%":[77],"compared":[78],"with":[79],"[1],and":[84],"update":[86],"cycle":[87],"fixed":[92],"to":[93],"4":[94],"clock":[95],"cycles.":[96]},"counts_by_year":[{"year":2023,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}