{"id":"https://openalex.org/W4387269743","doi":"https://doi.org/10.1109/asap57973.2023.00041","title":"AccMER: Accelerating Multi-Agent Experience Replay with Cache Locality-Aware Prioritization","display_name":"AccMER: Accelerating Multi-Agent Experience Replay with Cache Locality-Aware Prioritization","publication_year":2023,"publication_date":"2023-07-01","ids":{"openalex":"https://openalex.org/W4387269743","doi":"https://doi.org/10.1109/asap57973.2023.00041"},"language":"en","primary_location":{"id":"doi:10.1109/asap57973.2023.00041","is_oa":false,"landing_page_url":"https://doi.org/10.1109/asap57973.2023.00041","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 IEEE 34th International Conference on Application-specific Systems, Architectures and Processors (ASAP)","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/A5006897355","display_name":"Kailash Gogineni","orcid":"https://orcid.org/0000-0003-1865-5470"},"institutions":[{"id":"https://openalex.org/I193531525","display_name":"George Washington University","ror":"https://ror.org/00y4zzh67","country_code":"US","type":"education","lineage":["https://openalex.org/I193531525"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Kailash Gogineni","raw_affiliation_strings":["The George Washington University,Washington, DC,USA","The George Washington University, Washington, DC, USA"],"affiliations":[{"raw_affiliation_string":"The George Washington University,Washington, DC,USA","institution_ids":["https://openalex.org/I193531525"]},{"raw_affiliation_string":"The George Washington University, Washington, DC, USA","institution_ids":["https://openalex.org/I193531525"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5011252336","display_name":"Yongsheng Mei","orcid":"https://orcid.org/0000-0001-7606-8931"},"institutions":[{"id":"https://openalex.org/I193531525","display_name":"George Washington University","ror":"https://ror.org/00y4zzh67","country_code":"US","type":"education","lineage":["https://openalex.org/I193531525"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Yongsheng Mei","raw_affiliation_strings":["The George Washington University,Washington, DC,USA","The George Washington University, Washington, DC, USA"],"affiliations":[{"raw_affiliation_string":"The George Washington University,Washington, DC,USA","institution_ids":["https://openalex.org/I193531525"]},{"raw_affiliation_string":"The George Washington University, Washington, DC, USA","institution_ids":["https://openalex.org/I193531525"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5016639693","display_name":"L\u00fc Tian","orcid":"https://orcid.org/0000-0002-5893-0169"},"institutions":[{"id":"https://openalex.org/I193531525","display_name":"George Washington University","ror":"https://ror.org/00y4zzh67","country_code":"US","type":"education","lineage":["https://openalex.org/I193531525"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Tian Lan","raw_affiliation_strings":["The George Washington University,Washington, DC,USA","The George Washington University, Washington, DC, USA"],"affiliations":[{"raw_affiliation_string":"The George Washington University,Washington, DC,USA","institution_ids":["https://openalex.org/I193531525"]},{"raw_affiliation_string":"The George Washington University, Washington, DC, USA","institution_ids":["https://openalex.org/I193531525"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5019479187","display_name":"Wei Peng","orcid":"https://orcid.org/0000-0002-2892-5764"},"institutions":[{"id":"https://openalex.org/I193531525","display_name":"George Washington University","ror":"https://ror.org/00y4zzh67","country_code":"US","type":"education","lineage":["https://openalex.org/I193531525"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Peng Wei","raw_affiliation_strings":["The George Washington University,Washington, DC,USA","The George Washington University, Washington, DC, USA"],"affiliations":[{"raw_affiliation_string":"The George Washington University,Washington, DC,USA","institution_ids":["https://openalex.org/I193531525"]},{"raw_affiliation_string":"The George Washington University, Washington, DC, USA","institution_ids":["https://openalex.org/I193531525"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5045879054","display_name":"Guru Venkataramani","orcid":"https://orcid.org/0000-0002-7084-7560"},"institutions":[{"id":"https://openalex.org/I193531525","display_name":"George Washington University","ror":"https://ror.org/00y4zzh67","country_code":"US","type":"education","lineage":["https://openalex.org/I193531525"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Guru Venkataramani","raw_affiliation_strings":["The George Washington University,Washington, DC,USA","The George Washington University, Washington, DC, USA"],"affiliations":[{"raw_affiliation_string":"The George Washington University,Washington, DC,USA","institution_ids":["https://openalex.org/I193531525"]},{"raw_affiliation_string":"The George Washington University, Washington, DC, USA","institution_ids":["https://openalex.org/I193531525"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5006897355"],"corresponding_institution_ids":["https://openalex.org/I193531525"],"apc_list":null,"apc_paid":null,"fwci":0.8728,"has_fulltext":false,"cited_by_count":5,"citation_normalized_percentile":{"value":0.79033396,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":98},"biblio":{"volume":null,"issue":null,"first_page":"205","last_page":"212"},"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/T10249","display_name":"Distributed Control Multi-Agent Systems","score":0.998199999332428,"subfield":{"id":"https://openalex.org/subfields/1705","display_name":"Computer Networks and Communications"},"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/T13553","display_name":"Age of Information Optimization","score":0.9927999973297119,"subfield":{"id":"https://openalex.org/subfields/1705","display_name":"Computer Networks and Communications"},"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":0.841657817363739},{"id":"https://openalex.org/keywords/cache","display_name":"Cache","score":0.7611962556838989},{"id":"https://openalex.org/keywords/reinforcement-learning","display_name":"Reinforcement learning","score":0.7172365188598633},{"id":"https://openalex.org/keywords/cache-algorithms","display_name":"Cache algorithms","score":0.5178402066230774},{"id":"https://openalex.org/keywords/locality","display_name":"Locality","score":0.45840930938720703},{"id":"https://openalex.org/keywords/distributed-computing","display_name":"Distributed computing","score":0.4490007162094116},{"id":"https://openalex.org/keywords/thompson-sampling","display_name":"Thompson sampling","score":0.4409443438053131},{"id":"https://openalex.org/keywords/reuse","display_name":"Reuse","score":0.4399661123752594},{"id":"https://openalex.org/keywords/sampling","display_name":"Sampling (signal processing)","score":0.4181167483329773},{"id":"https://openalex.org/keywords/regret","display_name":"Regret","score":0.33831727504730225},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.33733057975769043},{"id":"https://openalex.org/keywords/parallel-computing","display_name":"Parallel computing","score":0.33653950691223145},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.30125826597213745},{"id":"https://openalex.org/keywords/cpu-cache","display_name":"CPU cache","score":0.21816551685333252}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.841657817363739},{"id":"https://openalex.org/C115537543","wikidata":"https://www.wikidata.org/wiki/Q165596","display_name":"Cache","level":2,"score":0.7611962556838989},{"id":"https://openalex.org/C97541855","wikidata":"https://www.wikidata.org/wiki/Q830687","display_name":"Reinforcement learning","level":2,"score":0.7172365188598633},{"id":"https://openalex.org/C38556500","wikidata":"https://www.wikidata.org/wiki/Q13404475","display_name":"Cache algorithms","level":4,"score":0.5178402066230774},{"id":"https://openalex.org/C2779808786","wikidata":"https://www.wikidata.org/wiki/Q6664603","display_name":"Locality","level":2,"score":0.45840930938720703},{"id":"https://openalex.org/C120314980","wikidata":"https://www.wikidata.org/wiki/Q180634","display_name":"Distributed computing","level":1,"score":0.4490007162094116},{"id":"https://openalex.org/C73602740","wikidata":"https://www.wikidata.org/wiki/Q7795822","display_name":"Thompson sampling","level":3,"score":0.4409443438053131},{"id":"https://openalex.org/C206588197","wikidata":"https://www.wikidata.org/wiki/Q846574","display_name":"Reuse","level":2,"score":0.4399661123752594},{"id":"https://openalex.org/C140779682","wikidata":"https://www.wikidata.org/wiki/Q210868","display_name":"Sampling (signal processing)","level":3,"score":0.4181167483329773},{"id":"https://openalex.org/C50817715","wikidata":"https://www.wikidata.org/wiki/Q79895177","display_name":"Regret","level":2,"score":0.33831727504730225},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.33733057975769043},{"id":"https://openalex.org/C173608175","wikidata":"https://www.wikidata.org/wiki/Q232661","display_name":"Parallel computing","level":1,"score":0.33653950691223145},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.30125826597213745},{"id":"https://openalex.org/C189783530","wikidata":"https://www.wikidata.org/wiki/Q352090","display_name":"CPU cache","level":3,"score":0.21816551685333252},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.0},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C18903297","wikidata":"https://www.wikidata.org/wiki/Q7150","display_name":"Ecology","level":1,"score":0.0},{"id":"https://openalex.org/C106131492","wikidata":"https://www.wikidata.org/wiki/Q3072260","display_name":"Filter (signal processing)","level":2,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/asap57973.2023.00041","is_oa":false,"landing_page_url":"https://doi.org/10.1109/asap57973.2023.00041","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 IEEE 34th International Conference on Application-specific Systems, Architectures and Processors (ASAP)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G7920894255","display_name":null,"funder_award_id":"CCF-2114415","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"}],"funders":[{"id":"https://openalex.org/F4320306076","display_name":"National Science Foundation","ror":"https://ror.org/021nxhr62"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":60,"referenced_works":["https://openalex.org/W1602154927","https://openalex.org/W2012812921","https://openalex.org/W2048226872","https://openalex.org/W2155007355","https://openalex.org/W2201581102","https://openalex.org/W2396783599","https://openalex.org/W2524428287","https://openalex.org/W2555255624","https://openalex.org/W2616729100","https://openalex.org/W2747213132","https://openalex.org/W2763421725","https://openalex.org/W2793035934","https://openalex.org/W2931767035","https://openalex.org/W2946901134","https://openalex.org/W2965870268","https://openalex.org/W3004268170","https://openalex.org/W3012148463","https://openalex.org/W3089506933","https://openalex.org/W3092209569","https://openalex.org/W3100764036","https://openalex.org/W3170435130","https://openalex.org/W3176265013","https://openalex.org/W3212207126","https://openalex.org/W4214717370","https://openalex.org/W4221145105","https://openalex.org/W4232019702","https://openalex.org/W4287755265","https://openalex.org/W4288095758","https://openalex.org/W4296611641","https://openalex.org/W4299802797","https://openalex.org/W4320559184","https://openalex.org/W4320700466","https://openalex.org/W4321592899","https://openalex.org/W4378464536","https://openalex.org/W6682849425","https://openalex.org/W6685444567","https://openalex.org/W6687681856","https://openalex.org/W6727208969","https://openalex.org/W6730065366","https://openalex.org/W6738174457","https://openalex.org/W6738796088","https://openalex.org/W6745245109","https://openalex.org/W6748554570","https://openalex.org/W6749032995","https://openalex.org/W6749304979","https://openalex.org/W6750645735","https://openalex.org/W6755069753","https://openalex.org/W6763177082","https://openalex.org/W6763300512","https://openalex.org/W6768731700","https://openalex.org/W6774948183","https://openalex.org/W6779380009","https://openalex.org/W6780135261","https://openalex.org/W6787618087","https://openalex.org/W6796258226","https://openalex.org/W6803771995","https://openalex.org/W6849717179","https://openalex.org/W6850089994","https://openalex.org/W6850147828","https://openalex.org/W6853536007"],"related_works":["https://openalex.org/W2031173804","https://openalex.org/W2041820064","https://openalex.org/W2009566782","https://openalex.org/W1524955365","https://openalex.org/W2509523906","https://openalex.org/W2100901045","https://openalex.org/W2114386333","https://openalex.org/W2138965869","https://openalex.org/W2147511796","https://openalex.org/W2354520536"],"abstract_inverted_index":{"Multi-Agent":[0],"Experience":[1],"Replay":[2],"(MER)":[3],"is":[4,96],"a":[5,42,97,131],"key":[6],"component":[7],"of":[8,28,133,152,194,212],"off-policy":[9],"reinforcement":[10,58],"learning":[11,33,59],"(RL)":[12],"algorithms.":[13],"By":[14],"remembering":[15],"and":[16,31,51,145],"reusing":[17,195],"experiences":[18],"from":[19],"the":[20,26,80,92,102,109,127,142,147,167,180,187,192,196,201,227],"past,":[21],"experience":[22,63],"replay":[23,64],"significantly":[24],"improves":[25],"stability":[27],"RL":[29],"algorithms":[30,61,222],"their":[32],"efficiency.":[34],"In":[35],"many":[36],"scenarios,":[37],"multiple":[38],"agents":[39],"interact":[40],"in":[41,79,114,138,226],"shared":[43],"environment":[44,190],"during":[45],"online":[46],"training":[47,50,209],"under":[48],"centralized":[49],"decentralized":[52],"execution":[53],"(CTDE)":[54],"paradigm.":[55],"Current":[56],"multi-agent":[57],"(MARL)":[60],"consider":[62],"with":[65],"uniform":[66],"sampling":[67,81,153],"or":[68],"based":[69,199],"on":[70,186,200],"priority":[71,163,202],"weights":[72,164],"to":[73,140,165,218],"improve":[74,141],"transition":[75,85,148],"data":[76,86,149],"sample":[77],"efficiency":[78],"phase.":[82],"However,":[83],"moving":[84],"histories":[87],"for":[88,130],"each":[89,157],"agent":[90],"through":[91],"processor":[93],"memory":[94],"hierarchy":[95],"performance":[98],"limiter.":[99],"Also,":[100],"as":[101],"agents'":[103],"transitions":[104,128,155,168,173,198],"continuously":[105],"renew":[106],"every":[107],"iteration,":[108],"finite":[110],"cache":[111,116,143,181],"capacity":[112],"results":[113,185],"increased":[115],"misses.":[117],"To":[118],"this":[119],"end,":[120],"we":[121,205],"propose":[122],"AccMER,":[123],"that":[124,170],"repeatedly":[125],"reuses":[126],"(experiences)":[129],"window":[132],"<tex":[134],"xmlns:mml=\"http://www.w3.org/1998/Math/MathML\"":[135],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">$n$</tex>":[136],"steps":[137],"order":[139],"locality":[144],"minimize":[146],"movement,":[150],"instead":[151],"new":[154],"at":[156],"step.":[158],"Specifically,":[159],"our":[160],"optimization":[161],"uses":[162],"select":[166],"so":[169],"only":[171],"high-priority":[172],"will":[174],"be":[175],"reused":[176],"frequently,":[177],"thereby":[178],"improving":[179],"performance.":[182],"Our":[183],"experimental":[184],"Predator-":[188],"Prey":[189],"demonstrate":[191],"effectiveness":[193],"essential":[197],"weights,":[203],"where":[204],"observe":[206],"an":[207],"end-to-end":[208],"time":[210],"reduction":[211],"25.4%":[213],"(for":[214],"32":[215],"agents)":[216],"compared":[217],"existing":[219],"prioritized":[220],"MER":[221],"without":[223],"notable":[224],"degradation":[225],"mean":[228],"reward.":[229]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":4}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
