{"id":"https://openalex.org/W4402727215","doi":"https://doi.org/10.1109/cis-ram61939.2024.10672803","title":"DEP-SNN-RL:Spiking Neural Networks Reinforcement Learning in Musculoskeletal Systems","display_name":"DEP-SNN-RL:Spiking Neural Networks Reinforcement Learning in Musculoskeletal Systems","publication_year":2024,"publication_date":"2024-08-08","ids":{"openalex":"https://openalex.org/W4402727215","doi":"https://doi.org/10.1109/cis-ram61939.2024.10672803"},"language":"en","primary_location":{"id":"doi:10.1109/cis-ram61939.2024.10672803","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cis-ram61939.2024.10672803","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 IEEE International Conference on Cybernetics and Intelligent Systems (CIS) and IEEE International Conference on Robotics, Automation and Mechatronics (RAM)","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/A5101622669","display_name":"Shuailong Li","orcid":"https://orcid.org/0000-0001-7864-6184"},"institutions":[{"id":"https://openalex.org/I4210123185","display_name":"Zhejiang Lab","ror":"https://ror.org/02m2h7991","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210123185"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Shuailong Li","raw_affiliation_strings":["Zhejiang Lab,Research Center for Frontier Fundamental Studies,Hangzhou,China"],"affiliations":[{"raw_affiliation_string":"Zhejiang Lab,Research Center for Frontier Fundamental Studies,Hangzhou,China","institution_ids":["https://openalex.org/I4210123185"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5009487709","display_name":"Qing Zhang","orcid":"https://orcid.org/0000-0002-5652-4036"},"institutions":[{"id":"https://openalex.org/I4210123185","display_name":"Zhejiang Lab","ror":"https://ror.org/02m2h7991","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210123185"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Qing Zhang","raw_affiliation_strings":["Zhejiang Lab,Research Center for Frontier Fundamental Studies,Hangzhou,China"],"affiliations":[{"raw_affiliation_string":"Zhejiang Lab,Research Center for Frontier Fundamental Studies,Hangzhou,China","institution_ids":["https://openalex.org/I4210123185"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100757894","display_name":"Lin Feng","orcid":null},"institutions":[{"id":"https://openalex.org/I4210123185","display_name":"Zhejiang Lab","ror":"https://ror.org/02m2h7991","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210123185"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Feng Lin","raw_affiliation_strings":["Zhejiang Lab,Research Center for Frontier Fundamental Studies,Hangzhou,China"],"affiliations":[{"raw_affiliation_string":"Zhejiang Lab,Research Center for Frontier Fundamental Studies,Hangzhou,China","institution_ids":["https://openalex.org/I4210123185"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5101622669"],"corresponding_institution_ids":["https://openalex.org/I4210123185"],"apc_list":null,"apc_paid":null,"fwci":0.7839,"has_fulltext":false,"cited_by_count":4,"citation_normalized_percentile":{"value":0.69187753,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":96,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"452","last_page":"456"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10784","display_name":"Muscle activation and electromyography studies","score":0.9987999796867371,"subfield":{"id":"https://openalex.org/subfields/2204","display_name":"Biomedical 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/T10784","display_name":"Muscle activation and electromyography studies","score":0.9987999796867371,"subfield":{"id":"https://openalex.org/subfields/2204","display_name":"Biomedical Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11601","display_name":"Neuroscience and Neural Engineering","score":0.9944999814033508,"subfield":{"id":"https://openalex.org/subfields/2804","display_name":"Cellular and Molecular Neuroscience"},"field":{"id":"https://openalex.org/fields/28","display_name":"Neuroscience"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},{"id":"https://openalex.org/T10502","display_name":"Advanced Memory and Neural Computing","score":0.9921000003814697,"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/reinforcement-learning","display_name":"Reinforcement learning","score":0.7639147043228149},{"id":"https://openalex.org/keywords/spiking-neural-network","display_name":"Spiking neural network","score":0.7476565837860107},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6891421675682068},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.49140965938568115},{"id":"https://openalex.org/keywords/reinforcement","display_name":"Reinforcement","score":0.45795994997024536},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4475272595882416},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.1496298909187317}],"concepts":[{"id":"https://openalex.org/C97541855","wikidata":"https://www.wikidata.org/wiki/Q830687","display_name":"Reinforcement learning","level":2,"score":0.7639147043228149},{"id":"https://openalex.org/C11731999","wikidata":"https://www.wikidata.org/wiki/Q9067355","display_name":"Spiking neural network","level":3,"score":0.7476565837860107},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6891421675682068},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.49140965938568115},{"id":"https://openalex.org/C67203356","wikidata":"https://www.wikidata.org/wiki/Q1321905","display_name":"Reinforcement","level":2,"score":0.45795994997024536},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4475272595882416},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.1496298909187317},{"id":"https://openalex.org/C66938386","wikidata":"https://www.wikidata.org/wiki/Q633538","display_name":"Structural engineering","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/cis-ram61939.2024.10672803","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cis-ram61939.2024.10672803","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 IEEE International Conference on Cybernetics and Intelligent Systems (CIS) and IEEE International Conference on Robotics, Automation and Mechatronics (RAM)","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":20,"referenced_works":["https://openalex.org/W1985940938","https://openalex.org/W2006370340","https://openalex.org/W2013469005","https://openalex.org/W2081030963","https://openalex.org/W2106423795","https://openalex.org/W2156432573","https://openalex.org/W2470342634","https://openalex.org/W2892077605","https://openalex.org/W2902174834","https://openalex.org/W2903079954","https://openalex.org/W2905533880","https://openalex.org/W2911276762","https://openalex.org/W2942634077","https://openalex.org/W2980764939","https://openalex.org/W3028840358","https://openalex.org/W3043133474","https://openalex.org/W3104342477","https://openalex.org/W3207905039","https://openalex.org/W4251657640","https://openalex.org/W4327862110"],"related_works":["https://openalex.org/W4310083477","https://openalex.org/W2328553770","https://openalex.org/W2920061524","https://openalex.org/W1977959518","https://openalex.org/W2038908348","https://openalex.org/W2107890255","https://openalex.org/W2106552856","https://openalex.org/W2145821588","https://openalex.org/W2086122291","https://openalex.org/W1987513656"],"abstract_inverted_index":{"Muscle-actuated":[0],"organisms":[1],"exhibit":[2],"an":[3,77,103],"extraordinary":[4],"ability":[5],"to":[6,29,41,82],"learn":[7],"a":[8,127,152],"wide":[9],"array":[10],"of":[11,32,65,97,109,122,145],"agile":[12],"movements.":[13],"However,":[14],"replicating":[15],"such":[16,57],"versatility":[17],"and":[18,84,132],"efficiency":[19,44,96],"in":[20,47,53,68,135,156],"reinforcement":[21,98,158],"learning":[22,99,134,159],"(RL)":[23],"poses":[24],"significant":[25,153],"challenges,":[26],"primarily":[27],"due":[28],"the":[30,42,51,63,88,94,106,120,143],"complexity":[31],"over-actuated":[33,69],"action":[34,59],"spaces.":[35],"These":[36],"challenges":[37],"are":[38],"often":[39],"attributed":[40],"sample":[43,95],"issues":[45],"prevalent":[46],"RL,":[48],"compounded":[49],"by":[50],"inefficacy":[52],"exploration":[54,67,86],"strategies":[55],"within":[56,161],"expansive":[58],"domains.":[60],"To":[61,91],"address":[62],"challenge":[64],"ineffective":[66],"spaces,":[70],"we":[71,101],"leverage":[72],"Differential":[73],"Extrinsic":[74],"Plasticity":[75],"(DEP),":[76],"innovative":[78],"self-organizing":[79],"mechanism":[80],"designed":[81],"enhance":[83],"expedite":[85],"across":[87],"state":[89],"space.":[90],"further":[92],"augment":[93],"techniques,":[100],"introduce":[102],"integration":[104],"with":[105],"third":[107],"generation":[108],"neural":[110],"networks,":[111],"namely":[112],"Spiking":[113],"Neural":[114],"Networks":[115],"(SNNs).":[116],"This":[117],"integration,":[118],"forming":[119],"core":[121],"our":[123],"DEP-RL":[124,147],"framework,":[125],"sets":[126],"new":[128],"benchmark":[129],"for":[130],"rapid":[131],"effective":[133],"musculoskeletal":[136],"systems.":[137],"Our":[138],"approach":[139],"not":[140],"only":[141],"surpasses":[142],"performance":[144],"conventional":[146],"methodologies":[148],"but":[149],"also":[150],"marks":[151],"leap":[154],"forward":[155],"advancing":[157],"capabilities":[160],"complex,":[162],"muscle-driven":[163],"biological":[164],"architectures.":[165]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":3}],"updated_date":"2025-12-27T23:08:20.325037","created_date":"2025-10-10T00:00:00"}
