{"id":"https://openalex.org/W4200346742","doi":"https://doi.org/10.1109/gcce53005.2021.9621852","title":"Proposal of Ephemeral Value Adjustment with Dimensionality Reduction in Deep Reinforcement Learning","display_name":"Proposal of Ephemeral Value Adjustment with Dimensionality Reduction in Deep Reinforcement Learning","publication_year":2021,"publication_date":"2021-10-12","ids":{"openalex":"https://openalex.org/W4200346742","doi":"https://doi.org/10.1109/gcce53005.2021.9621852"},"language":"en","primary_location":{"id":"doi:10.1109/gcce53005.2021.9621852","is_oa":false,"landing_page_url":"https://doi.org/10.1109/gcce53005.2021.9621852","pdf_url":null,"source":{"id":"https://openalex.org/S4363607807","display_name":"2021 IEEE 10th Global Conference on Consumer Electronics (GCCE)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 IEEE 10th Global Conference on Consumer Electronics (GCCE)","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/A5083622472","display_name":"Daiki Kuyoshi","orcid":null},"institutions":[{"id":"https://openalex.org/I10091056","display_name":"Kanazawa University","ror":"https://ror.org/02hwp6a56","country_code":"JP","type":"education","lineage":["https://openalex.org/I10091056"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Daiki Kuyoshi","raw_affiliation_strings":["Kanazawa University, Kanazawa, Japan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Kanazawa University, Kanazawa, Japan","institution_ids":["https://openalex.org/I10091056"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101989123","display_name":"Yuta Suzuki","orcid":"https://orcid.org/0000-0002-0019-4832"},"institutions":[{"id":"https://openalex.org/I10091056","display_name":"Kanazawa University","ror":"https://ror.org/02hwp6a56","country_code":"JP","type":"education","lineage":["https://openalex.org/I10091056"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Yuta Suzuki","raw_affiliation_strings":["Kanazawa University, Kanazawa, Japan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Kanazawa University, Kanazawa, Japan","institution_ids":["https://openalex.org/I10091056"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5102728648","display_name":"Satoshi Yamane","orcid":"https://orcid.org/0000-0001-7883-4054"},"institutions":[{"id":"https://openalex.org/I10091056","display_name":"Kanazawa University","ror":"https://ror.org/02hwp6a56","country_code":"JP","type":"education","lineage":["https://openalex.org/I10091056"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Satoshi Yamane","raw_affiliation_strings":["Kanazawa University, Kanazawa, Japan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Kanazawa University, Kanazawa, Japan","institution_ids":["https://openalex.org/I10091056"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.16053604,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"70","issue":null,"first_page":"672","last_page":"674"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10462","display_name":"Reinforcement Learning in Robotics","score":0.9976999759674072,"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":0.9976999759674072,"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/T11975","display_name":"Evolutionary Algorithms and Applications","score":0.9970999956130981,"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/T10848","display_name":"Advanced Multi-Objective Optimization Algorithms","score":0.9603000283241272,"subfield":{"id":"https://openalex.org/subfields/1703","display_name":"Computational Theory and Mathematics"},"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/ephemeral-key","display_name":"Ephemeral key","score":0.8774648904800415},{"id":"https://openalex.org/keywords/reinforcement-learning","display_name":"Reinforcement learning","score":0.840329110622406},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7452701926231384},{"id":"https://openalex.org/keywords/random-projection","display_name":"Random projection","score":0.6105160713195801},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6052457094192505},{"id":"https://openalex.org/keywords/curse-of-dimensionality","display_name":"Curse of dimensionality","score":0.5812132358551025},{"id":"https://openalex.org/keywords/dimensionality-reduction","display_name":"Dimensionality reduction","score":0.5350554585456848},{"id":"https://openalex.org/keywords/value","display_name":"Value (mathematics)","score":0.47539815306663513},{"id":"https://openalex.org/keywords/reinforcement","display_name":"Reinforcement","score":0.4586913287639618},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4399804472923279},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.14197692275047302},{"id":"https://openalex.org/keywords/psychology","display_name":"Psychology","score":0.12460952997207642}],"concepts":[{"id":"https://openalex.org/C76947770","wikidata":"https://www.wikidata.org/wiki/Q4533181","display_name":"Ephemeral key","level":2,"score":0.8774648904800415},{"id":"https://openalex.org/C97541855","wikidata":"https://www.wikidata.org/wiki/Q830687","display_name":"Reinforcement learning","level":2,"score":0.840329110622406},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7452701926231384},{"id":"https://openalex.org/C2777036070","wikidata":"https://www.wikidata.org/wiki/Q18393452","display_name":"Random projection","level":2,"score":0.6105160713195801},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6052457094192505},{"id":"https://openalex.org/C111030470","wikidata":"https://www.wikidata.org/wiki/Q1430460","display_name":"Curse of dimensionality","level":2,"score":0.5812132358551025},{"id":"https://openalex.org/C70518039","wikidata":"https://www.wikidata.org/wiki/Q16000077","display_name":"Dimensionality reduction","level":2,"score":0.5350554585456848},{"id":"https://openalex.org/C2776291640","wikidata":"https://www.wikidata.org/wiki/Q2912517","display_name":"Value (mathematics)","level":2,"score":0.47539815306663513},{"id":"https://openalex.org/C67203356","wikidata":"https://www.wikidata.org/wiki/Q1321905","display_name":"Reinforcement","level":2,"score":0.4586913287639618},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4399804472923279},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.14197692275047302},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.12460952997207642},{"id":"https://openalex.org/C77805123","wikidata":"https://www.wikidata.org/wiki/Q161272","display_name":"Social psychology","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/gcce53005.2021.9621852","is_oa":false,"landing_page_url":"https://doi.org/10.1109/gcce53005.2021.9621852","pdf_url":null,"source":{"id":"https://openalex.org/S4363607807","display_name":"2021 IEEE 10th Global Conference on Consumer Electronics (GCCE)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 IEEE 10th Global Conference on Consumer Electronics (GCCE)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":13,"referenced_works":["https://openalex.org/W2145339207","https://openalex.org/W2436711315","https://openalex.org/W2927014686","https://openalex.org/W2964082094","https://openalex.org/W3114470652","https://openalex.org/W3129949865","https://openalex.org/W4289376774","https://openalex.org/W4297732320","https://openalex.org/W6718359804","https://openalex.org/W6734330393","https://openalex.org/W6754857033","https://openalex.org/W6761032199","https://openalex.org/W6780559895"],"related_works":["https://openalex.org/W1995622179","https://openalex.org/W2790862734","https://openalex.org/W1552543208","https://openalex.org/W345943785","https://openalex.org/W2074396517","https://openalex.org/W2166963679","https://openalex.org/W2187269125","https://openalex.org/W2141406155","https://openalex.org/W1641615907","https://openalex.org/W3015962327"],"abstract_inverted_index":{"In":[0,15,31],"recent":[1],"years,":[2],"many":[3],"episodic":[4,22],"memory-based":[5],"methods":[6],"have":[7],"been":[8],"developed":[9],"in":[10],"deep":[11],"reinforcement":[12],"learning":[13,67],"research.":[14],"particular,":[16],"Ephemeral":[17],"Value":[18],"Adjustment":[19],"(EVA)":[20],"utilizes":[21],"memory":[23,58],"to":[24],"judge":[25],"behavior":[26],"and":[27,36,60],"improve":[28],"sample":[29],"efficiency.":[30],"this":[32],"paper,":[33],"we":[34],"propose":[35],"evaluate":[37],"a":[38],"method":[39],"that":[40],"reduces":[41],"the":[42,45,57,66],"dimensionality":[43],"of":[44],"keys":[46],"using":[47],"random":[48],"projection":[49],"for":[50],"EVA.":[51],"The":[52],"main":[53],"purpose":[54],"is":[55],"reducing":[56],"usage":[59],"more":[61],"efficient":[62],"lookup":[63],"with":[64],"maintaining":[65],"performance.":[68]},"counts_by_year":[],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}
