{"id":"https://openalex.org/W2924445828","doi":"https://doi.org/10.1145/3321707.3321723","title":"Learning with delayed synaptic plasticity","display_name":"Learning with delayed synaptic plasticity","publication_year":2019,"publication_date":"2019-07-03","ids":{"openalex":"https://openalex.org/W2924445828","doi":"https://doi.org/10.1145/3321707.3321723","mag":"2924445828"},"language":"en","primary_location":{"id":"doi:10.1145/3321707.3321723","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3321707.3321723","pdf_url":null,"source":{"id":"https://openalex.org/S4363608932","display_name":"Proceedings of the Genetic and Evolutionary Computation Conference","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":"Proceedings of the Genetic and Evolutionary Computation Conference","raw_type":"proceedings-article"},"type":"conference-paper","indexed_in":["arxiv","crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/1903.09393","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":null,"display_name":"Anil Yaman","orcid":null},"institutions":[{"id":"https://openalex.org/I83019370","display_name":"Eindhoven University of Technology","ror":"https://ror.org/02c2kyt77","country_code":"NL","type":"education","lineage":["https://openalex.org/I83019370"]}],"countries":["NL"],"is_corresponding":false,"raw_author_name":"Anil Yaman","raw_affiliation_strings":["Eindhoven University of Technology, Eindhoven, the Netherlands"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Eindhoven University of Technology, Eindhoven, the Netherlands","institution_ids":["https://openalex.org/I83019370"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Giovanni Iacca","orcid":null},"institutions":[{"id":"https://openalex.org/I193223587","display_name":"University of Trento","ror":"https://ror.org/05trd4x28","country_code":"IT","type":"education","lineage":["https://openalex.org/I193223587"]}],"countries":["IT"],"is_corresponding":false,"raw_author_name":"Giovanni Iacca","raw_affiliation_strings":["University of Trento, Trento, Italy"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Trento, Trento, Italy","institution_ids":["https://openalex.org/I193223587"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Decebal Constantin Mocanu","orcid":null},"institutions":[{"id":"https://openalex.org/I83019370","display_name":"Eindhoven University of Technology","ror":"https://ror.org/02c2kyt77","country_code":"NL","type":"education","lineage":["https://openalex.org/I83019370"]}],"countries":["NL"],"is_corresponding":false,"raw_author_name":"Decebal Constantin Mocanu","raw_affiliation_strings":["Eindhoven University of Technology, Eindhoven, the Netherlands"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Eindhoven University of Technology, Eindhoven, the Netherlands","institution_ids":["https://openalex.org/I83019370"]}]},{"author_position":"middle","author":{"id":null,"display_name":"George Fletcher","orcid":null},"institutions":[{"id":"https://openalex.org/I83019370","display_name":"Eindhoven University of Technology","ror":"https://ror.org/02c2kyt77","country_code":"NL","type":"education","lineage":["https://openalex.org/I83019370"]}],"countries":["NL"],"is_corresponding":false,"raw_author_name":"George Fletcher","raw_affiliation_strings":["Eindhoven University of Technology, Eindhoven, the Netherlands"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Eindhoven University of Technology, Eindhoven, the Netherlands","institution_ids":["https://openalex.org/I83019370"]}]},{"author_position":"last","author":{"id":null,"display_name":"Mykola Pechenizkiy","orcid":null},"institutions":[{"id":"https://openalex.org/I83019370","display_name":"Eindhoven University of Technology","ror":"https://ror.org/02c2kyt77","country_code":"NL","type":"education","lineage":["https://openalex.org/I83019370"]}],"countries":["NL"],"is_corresponding":false,"raw_author_name":"Mykola Pechenizkiy","raw_affiliation_strings":["Eindhoven University of Technology, Eindhoven, the Netherlands"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Eindhoven University of Technology, Eindhoven, the Netherlands","institution_ids":["https://openalex.org/I83019370"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":1.195,"has_fulltext":true,"cited_by_count":5,"citation_normalized_percentile":{"value":0.72573114,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":96},"biblio":{"volume":null,"issue":null,"first_page":"152","last_page":"160"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10502","display_name":"Advanced Memory and Neural Computing","score":0.5782999992370605,"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/T10502","display_name":"Advanced Memory and Neural Computing","score":0.5782999992370605,"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"}},{"id":"https://openalex.org/T10581","display_name":"Neural dynamics and brain function","score":0.06790000200271606,"subfield":{"id":"https://openalex.org/subfields/2805","display_name":"Cognitive 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/T10320","display_name":"Neural Networks and Applications","score":0.05559999868273735,"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/hebbian-theory","display_name":"Hebbian theory","score":0.7570000290870667},{"id":"https://openalex.org/keywords/reinforcement-learning","display_name":"Reinforcement learning","score":0.7436000108718872},{"id":"https://openalex.org/keywords/synaptic-plasticity","display_name":"Synaptic plasticity","score":0.565500020980835},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.5152000188827515},{"id":"https://openalex.org/keywords/metaplasticity","display_name":"Metaplasticity","score":0.47540000081062317},{"id":"https://openalex.org/keywords/synapse","display_name":"Synapse","score":0.4374000132083893},{"id":"https://openalex.org/keywords/reinforcement","display_name":"Reinforcement","score":0.4253000020980835},{"id":"https://openalex.org/keywords/spike-timing-dependent-plasticity","display_name":"Spike-timing-dependent plasticity","score":0.4142000079154968}],"concepts":[{"id":"https://openalex.org/C111437709","wikidata":"https://www.wikidata.org/wiki/Q1277874","display_name":"Hebbian theory","level":3,"score":0.7570000290870667},{"id":"https://openalex.org/C97541855","wikidata":"https://www.wikidata.org/wiki/Q830687","display_name":"Reinforcement learning","level":2,"score":0.7436000108718872},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6640999913215637},{"id":"https://openalex.org/C98229152","wikidata":"https://www.wikidata.org/wiki/Q1551556","display_name":"Synaptic plasticity","level":3,"score":0.565500020980835},{"id":"https://openalex.org/C169760540","wikidata":"https://www.wikidata.org/wiki/Q207011","display_name":"Neuroscience","level":1,"score":0.5297999978065491},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.5152000188827515},{"id":"https://openalex.org/C194973443","wikidata":"https://www.wikidata.org/wiki/Q1420291","display_name":"Metaplasticity","level":4,"score":0.47540000081062317},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4453999996185303},{"id":"https://openalex.org/C127445978","wikidata":"https://www.wikidata.org/wiki/Q187181","display_name":"Synapse","level":2,"score":0.4374000132083893},{"id":"https://openalex.org/C67203356","wikidata":"https://www.wikidata.org/wiki/Q1321905","display_name":"Reinforcement","level":2,"score":0.4253000020980835},{"id":"https://openalex.org/C159919123","wikidata":"https://www.wikidata.org/wiki/Q7577157","display_name":"Spike-timing-dependent plasticity","level":4,"score":0.4142000079154968},{"id":"https://openalex.org/C189950617","wikidata":"https://www.wikidata.org/wiki/Q937228","display_name":"Property (philosophy)","level":2,"score":0.37940001487731934},{"id":"https://openalex.org/C83119035","wikidata":"https://www.wikidata.org/wiki/Q17030659","display_name":"Homosynaptic plasticity","level":5,"score":0.3783000111579895},{"id":"https://openalex.org/C26410512","wikidata":"https://www.wikidata.org/wiki/Q3906363","display_name":"Nonsynaptic plasticity","level":5,"score":0.33799999952316284},{"id":"https://openalex.org/C79186407","wikidata":"https://www.wikidata.org/wiki/Q472074","display_name":"Plasticity","level":2,"score":0.3319000005722046},{"id":"https://openalex.org/C47611674","wikidata":"https://www.wikidata.org/wiki/Q849491","display_name":"Neuroplasticity","level":2,"score":0.3190000057220459},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3125999867916107},{"id":"https://openalex.org/C2993191138","wikidata":"https://www.wikidata.org/wiki/Q849491","display_name":"Structural plasticity","level":2,"score":0.3050999939441681},{"id":"https://openalex.org/C66949984","wikidata":"https://www.wikidata.org/wiki/Q7662043","display_name":"Synaptic weight","level":3,"score":0.2962999939918518},{"id":"https://openalex.org/C150720761","wikidata":"https://www.wikidata.org/wiki/Q7002465","display_name":"Neuronal memory allocation","level":5,"score":0.2953000068664551},{"id":"https://openalex.org/C120822770","wikidata":"https://www.wikidata.org/wiki/Q5156355","display_name":"Competitive learning","level":3,"score":0.2903999984264374},{"id":"https://openalex.org/C2778794669","wikidata":"https://www.wikidata.org/wiki/Q43054","display_name":"Neuron","level":2,"score":0.289000004529953},{"id":"https://openalex.org/C97108695","wikidata":"https://www.wikidata.org/wiki/Q6508265","display_name":"Leabra","level":5,"score":0.28769999742507935}],"mesh":[],"locations_count":6,"locations":[{"id":"doi:10.1145/3321707.3321723","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3321707.3321723","pdf_url":null,"source":{"id":"https://openalex.org/S4363608932","display_name":"Proceedings of the Genetic and Evolutionary Computation Conference","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":"Proceedings of the Genetic and Evolutionary Computation Conference","raw_type":"proceedings-article"},{"id":"pmh:oai:arXiv.org:1903.09393","is_oa":true,"landing_page_url":"http://arxiv.org/abs/1903.09393","pdf_url":"https://arxiv.org/pdf/1903.09393","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},{"id":"pmh:oai:iris.unitn.it:11572/251757","is_oa":true,"landing_page_url":"http://hdl.handle.net/11572/251757","pdf_url":"https://iris.unitn.it/bitstream/11572/251757/1/Learning_with_Delayed_Synaptic_Plasticity.pdf","source":{"id":"https://openalex.org/S4377196320","display_name":"Iris (University of Trento)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I193223587","host_organization_name":"University of Trento","host_organization_lineage":["https://openalex.org/I193223587"],"host_organization_lineage_names":[],"type":"repository"},"license":"other-oa","license_id":"https://openalex.org/licenses/other-oa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"info:eu-repo/semantics/conferenceObject"},{"id":"pmh:oai:pure.tue.nl:openaire_cris_publications/b900187f-695f-4031-95d2-22945813ea90","is_oa":true,"landing_page_url":"https://research.tue.nl/en/publications/b900187f-695f-4031-95d2-22945813ea90","pdf_url":"https://pure.tue.nl/ws/files/136763570/1903.09393.pdf","source":{"id":"https://openalex.org/S4406922641","display_name":"TU/e Research Portal","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":"repository"},"license":"other-oa","license_id":"https://openalex.org/licenses/other-oa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Yaman, A, Iacca, G, Mocanu, D C, Fletcher, G H L & Pechenizkiy, M 2019, Learning with delayed synaptic plasticity. in GECCO 2019 - Proceedings of the 2019 Genetic and Evolutionary Computation Conference. Association for Computing Machinery, Inc., New York, pp. 152-160, 2019 Genetic and Evolutionary Computation Conference, GECCO 2019, Prague, Czech Republic, 13/07/19. https://doi.org/10.1145/3321707.3321723","raw_type":"info:eu-repo/semantics/conferenceObject"},{"id":"pmh:oai:pure.tue.nl:publications/b900187f-695f-4031-95d2-22945813ea90","is_oa":true,"landing_page_url":"http://www.scopus.com/inward/record.url?scp=85072338773&partnerID=8YFLogxK","pdf_url":null,"source":{"id":"https://openalex.org/S4406922641","display_name":"TU/e Research Portal","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":"repository"},"license":"other-oa","license_id":"https://openalex.org/licenses/other-oa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Yaman, A, Iacca, G, Mocanu, D C, Fletcher, G H L & Pechenizkiy, M 2019, Learning with delayed synaptic plasticity. in GECCO 2019 - Proceedings of the 2019 Genetic and Evolutionary Computation Conference. Association for Computing Machinery, Inc., New York, pp. 152-160, 2019 Genetic and Evolutionary Computation Conference, GECCO 2019, Prague, Czech Republic, 13/07/19. https://doi.org/10.1145/3321707.3321723","raw_type":"info:eu-repo/semantics/conferenceObject"},{"id":"pmh:tue:oai:pure.tue.nl:publications/b900187f-695f-4031-95d2-22945813ea90","is_oa":true,"landing_page_url":"https://research.tue.nl/nl/publications/b900187f-695f-4031-95d2-22945813ea90","pdf_url":null,"source":{"id":"https://openalex.org/S4406922641","display_name":"TU/e Research Portal","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":"repository"},"license":"other-oa","license_id":"https://openalex.org/licenses/other-oa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"GECCO 2019 - Proceedings of the 2019 Genetic and Evolutionary Computation Conference, 152 - 160","raw_type":"info:eu-repo/semantics/conferencepaper"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:1903.09393","is_oa":true,"landing_page_url":"http://arxiv.org/abs/1903.09393","pdf_url":"https://arxiv.org/pdf/1903.09393","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G434337789","display_name":null,"funder_award_id":"HORIZON2020","funder_id":"https://openalex.org/F4320320300","funder_display_name":"European Commission"},{"id":"https://openalex.org/G6804535696","display_name":"Exploring the Unknown through Reincarnation and Co-evolution","funder_award_id":"665347","funder_id":"https://openalex.org/F4320320300","funder_display_name":"European Commission"}],"funders":[{"id":"https://openalex.org/F4320320300","display_name":"European Commission","ror":"https://ror.org/00k4n6c32"},{"id":"https://openalex.org/F4320338336","display_name":"H2020 Future and Emerging Technologies","ror":null}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":20,"referenced_works":["https://openalex.org/W1935590542","https://openalex.org/W1986021461","https://openalex.org/W1991157172","https://openalex.org/W1992678399","https://openalex.org/W2020399841","https://openalex.org/W2044724603","https://openalex.org/W2052363954","https://openalex.org/W2097791387","https://openalex.org/W2103610940","https://openalex.org/W2116412024","https://openalex.org/W2141740078","https://openalex.org/W2154607505","https://openalex.org/W2171658832","https://openalex.org/W2235406241","https://openalex.org/W2605353576","https://openalex.org/W2782973718","https://openalex.org/W2796541468","https://openalex.org/W2808133870","https://openalex.org/W2906697496","https://openalex.org/W4242770316"],"related_works":[],"abstract_inverted_index":{"The":[0],"plasticity":[1,23,85,145],"property":[2],"of":[3,98,114,117],"biological":[4],"neural":[5,29],"networks":[6,30],"allows":[7],"them":[8],"to":[9,67,74,87,103,111,129,141,195],"perform":[10,149],"learning":[11,34,89],"and":[12,46,148,155,178],"optimize":[13],"their":[14,18],"behavior":[15],"by":[16,21,31,185],"changing":[17],"configuration.":[19],"Inspired":[20],"biology,":[22],"can":[24],"be":[25],"modeled":[26],"in":[27,90,108],"artificial":[28],"using":[32],"Hebbian":[33,84],"rules,":[35],"i.e.":[36],"rules":[37,86,147,188],"that":[38,72,168,180],"update":[39],"synapses":[40],"based":[41,152],"on":[42,153],"the":[43,50,56,69,76,96,115,118,130,134,176,181,186,196],"neuron":[44,70,99],"activations":[45,71],"reinforcement":[47,57,77,121,157],"signals.":[48,158],"However,":[49],"distal":[51,91],"reward":[52,92],"problem":[53],"arises":[54],"when":[55],"signals":[58,122],"are":[59,123],"not":[60,170],"available":[61],"immediately":[62],"after":[63,125],"each":[64,109,126],"network":[65],"output":[66],"associate":[68],"contributed":[73],"receiving":[75],"signal.":[78],"In":[79],"this":[80],"work,":[81],"we":[82],"extend":[83],"allow":[88],"cases.":[93],"We":[94,137,159],"propose":[95],"use":[97],"activation":[100,116],"traces":[101],"(NATs)":[102],"provide":[104],"additional":[105],"data":[106],"storage":[107],"synapse":[110],"keep":[112],"track":[113],"neurons.":[119],"Delayed":[120],"provided":[124],"episode":[127],"relative":[128,194],"networks'":[131],"performance":[132,193],"during":[133],"previous":[135],"episode.":[136],"employ":[138],"genetic":[139],"algorithms":[140],"evolve":[142],"delayed":[143,156],"synaptic":[144,150,182],"(DSP)":[146],"updates":[151,183],"NATs":[154],"compare":[160],"DSP":[161,187],"with":[162,175],"an":[163],"analogous":[164],"hill":[165],"climbing":[166],"algorithm":[167],"does":[169],"incorporate":[171],"domain":[172],"knowledge":[173],"introduced":[174],"NATs,":[177],"show":[179],"performed":[184],"demonstrate":[189],"more":[190],"effective":[191],"training":[192],"HC":[197],"algorithm.":[198]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2024,"cited_by_count":1},{"year":2021,"cited_by_count":2},{"year":2020,"cited_by_count":1}],"updated_date":"2026-08-29T07:29:34.045763","created_date":"2019-04-01T00:00:00"}
