{"id":"https://openalex.org/W4378501252","doi":"https://doi.org/10.1145/3583131.3590460","title":"Learning to Act through Evolution of Neural Diversity in Random Neural Networks","display_name":"Learning to Act through Evolution of Neural Diversity in Random Neural Networks","publication_year":2023,"publication_date":"2023-07-12","ids":{"openalex":"https://openalex.org/W4378501252","doi":"https://doi.org/10.1145/3583131.3590460"},"language":"en","primary_location":{"id":"doi:10.1145/3583131.3590460","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3583131.3590460","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/2305.15945","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5090011209","display_name":"Joachim Winther Pedersen","orcid":"https://orcid.org/0000-0001-7884-9432"},"institutions":[{"id":"https://openalex.org/I83467386","display_name":"IT University of Copenhagen","ror":"https://ror.org/02309jg23","country_code":"DK","type":"education","lineage":["https://openalex.org/I83467386"]}],"countries":["DK"],"is_corresponding":false,"raw_author_name":"Joachim Pedersen","raw_affiliation_strings":["Digital Design, IT University of Copenhagen, Copenhagen, Denmark"],"raw_orcid":"https://orcid.org/0000-0001-7884-9432","affiliations":[{"raw_affiliation_string":"Digital Design, IT University of Copenhagen, Copenhagen, Denmark","institution_ids":["https://openalex.org/I83467386"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5020511097","display_name":"Sebastian Risi","orcid":"https://orcid.org/0000-0003-3607-8400"},"institutions":[{"id":"https://openalex.org/I83467386","display_name":"IT University of Copenhagen","ror":"https://ror.org/02309jg23","country_code":"DK","type":"education","lineage":["https://openalex.org/I83467386"]}],"countries":["DK"],"is_corresponding":false,"raw_author_name":"Sebastian Risi","raw_affiliation_strings":["Digital Design, IT University of Copenhagen, Copenhagen, Denmark"],"raw_orcid":"https://orcid.org/0000-0003-3607-8400","affiliations":[{"raw_affiliation_string":"Digital Design, IT University of Copenhagen, Copenhagen, Denmark","institution_ids":["https://openalex.org/I83467386"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I83467386"],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":true,"cited_by_count":2,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1248","last_page":"1256"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10502","display_name":"Advanced Memory and Neural Computing","score":0.9997000098228455,"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":0.9997000098228455,"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/T10320","display_name":"Neural Networks and Applications","score":0.9986000061035156,"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/T12808","display_name":"Ferroelectric and Negative Capacitance Devices","score":0.9986000061035156,"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/artificial-neural-network","display_name":"Artificial neural network","score":0.8090723156929016},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7535920143127441},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6212799549102783},{"id":"https://openalex.org/keywords/nervous-system-network-models","display_name":"Nervous system network models","score":0.5700393915176392},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.5380973219871521},{"id":"https://openalex.org/keywords/reinforcement-learning","display_name":"Reinforcement learning","score":0.5269967913627625},{"id":"https://openalex.org/keywords/stochastic-neural-network","display_name":"Stochastic neural network","score":0.5128276944160461},{"id":"https://openalex.org/keywords/types-of-artificial-neural-networks","display_name":"Types of artificial neural networks","score":0.4876162111759186},{"id":"https://openalex.org/keywords/recurrent-neural-network","display_name":"Recurrent neural network","score":0.4119330644607544},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3906796872615814}],"concepts":[{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.8090723156929016},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7535920143127441},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6212799549102783},{"id":"https://openalex.org/C173079777","wikidata":"https://www.wikidata.org/wiki/Q4299350","display_name":"Nervous system network models","level":5,"score":0.5700393915176392},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.5380973219871521},{"id":"https://openalex.org/C97541855","wikidata":"https://www.wikidata.org/wiki/Q830687","display_name":"Reinforcement learning","level":2,"score":0.5269967913627625},{"id":"https://openalex.org/C86582703","wikidata":"https://www.wikidata.org/wiki/Q7617824","display_name":"Stochastic neural network","level":4,"score":0.5128276944160461},{"id":"https://openalex.org/C177973122","wikidata":"https://www.wikidata.org/wiki/Q7860946","display_name":"Types of artificial neural networks","level":4,"score":0.4876162111759186},{"id":"https://openalex.org/C147168706","wikidata":"https://www.wikidata.org/wiki/Q1457734","display_name":"Recurrent neural network","level":3,"score":0.4119330644607544},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3906796872615814},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1145/3583131.3590460","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3583131.3590460","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:2305.15945","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2305.15945","pdf_url":"https://arxiv.org/pdf/2305.15945","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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:2305.15945","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2305.15945","pdf_url":"https://arxiv.org/pdf/2305.15945","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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4378501252.pdf","grobid_xml":"https://content.openalex.org/works/W4378501252.grobid-xml"},"referenced_works_count":67,"referenced_works":["https://openalex.org/W169981133","https://openalex.org/W204562716","https://openalex.org/W607572140","https://openalex.org/W1485981043","https://openalex.org/W1489333352","https://openalex.org/W1566892458","https://openalex.org/W1576838367","https://openalex.org/W1577932924","https://openalex.org/W1627056129","https://openalex.org/W1677182931","https://openalex.org/W2022945991","https://openalex.org/W2052363954","https://openalex.org/W2058918256","https://openalex.org/W2078525842","https://openalex.org/W2091565802","https://openalex.org/W2111935653","https://openalex.org/W2118020688","https://openalex.org/W2128432504","https://openalex.org/W2141487738","https://openalex.org/W2143200432","https://openalex.org/W2144212877","https://openalex.org/W2163922914","https://openalex.org/W2164653071","https://openalex.org/W2429018336","https://openalex.org/W2486606926","https://openalex.org/W2544817431","https://openalex.org/W2596367596","https://openalex.org/W2605216006","https://openalex.org/W2605353576","https://openalex.org/W2738724892","https://openalex.org/W2783637861","https://openalex.org/W2798878556","https://openalex.org/W2805003733","https://openalex.org/W2897058286","https://openalex.org/W2898323475","https://openalex.org/W2934533499","https://openalex.org/W2946037774","https://openalex.org/W2947265751","https://openalex.org/W2948635472","https://openalex.org/W2962965870","https://openalex.org/W2964199361","https://openalex.org/W2994827227","https://openalex.org/W3015661699","https://openalex.org/W3034234149","https://openalex.org/W3038944566","https://openalex.org/W3085139254","https://openalex.org/W3094858753","https://openalex.org/W3167683307","https://openalex.org/W3174753037","https://openalex.org/W3189057580","https://openalex.org/W3207210182","https://openalex.org/W4205694016","https://openalex.org/W4234552385","https://openalex.org/W4251023430","https://openalex.org/W4254816979","https://openalex.org/W4256333068","https://openalex.org/W4287727148","https://openalex.org/W4287752407","https://openalex.org/W4288333794","https://openalex.org/W4289709979","https://openalex.org/W4291786841","https://openalex.org/W4300011764","https://openalex.org/W4302028573","https://openalex.org/W4394665603","https://openalex.org/W4394666657","https://openalex.org/W6775837273","https://openalex.org/W6780069234"],"related_works":["https://openalex.org/W2373874059","https://openalex.org/W2950022897","https://openalex.org/W2533573066","https://openalex.org/W1538606284","https://openalex.org/W1973323485","https://openalex.org/W180587397","https://openalex.org/W2378845890","https://openalex.org/W1584270863","https://openalex.org/W1595652908","https://openalex.org/W1538193578"],"abstract_inverted_index":{"Biological":[0],"nervous":[1],"systems":[2],"consist":[3],"of":[4,6,14,16,49,62,69,80],"networks":[5,23],"diverse,":[7],"sophisticated":[8],"information":[9],"processors":[10],"in":[11,136],"the":[12,45,60,78,81,119,129],"form":[13],"neurons":[15,39,71,113],"different":[17],"classes.":[18],"In":[19,55],"most":[20],"artificial":[21],"neural":[22,25,87,134,138,153],"(ANNs),":[24],"computation":[26],"is":[27,34],"abstracted":[28],"to":[29,65,92,106,114,125],"an":[30,108],"activation":[31],"function":[32],"that":[33,72,85],"usually":[35],"shared":[36],"between":[37],"all":[38],"within":[40],"a":[41,67,115],"layer":[42],"or":[43],"even":[44],"whole":[46],"network;":[47],"training":[48],"ANNs":[50],"focuses":[51],"on":[52],"synaptic":[53,101],"optimization.":[54],"this":[56],"paper,":[57],"we":[58,83],"propose":[59],"optimization":[61],"neuro-centric":[63],"parameters":[64,88],"attain":[66],"set":[68],"diverse":[70],"can":[73],"perform":[74],"complex":[75],"computations.":[76],"Demonstrating":[77],"promise":[79],"approach,":[82],"show":[84],"evolving":[86],"alone":[89],"allows":[90,123],"agents":[91],"solve":[93],"various":[94],"reinforcement":[95],"learning":[96],"tasks":[97],"without":[98],"optimizing":[99],"any":[100],"weights.":[102],"While":[103],"not":[104],"aiming":[105],"be":[107],"accurate":[109],"biological":[110],"model,":[111],"parameterizing":[112],"larger":[116],"degree":[117],"than":[118],"current":[120],"common":[121],"practice,":[122],"us":[124],"ask":[126],"questions":[127],"about":[128],"computational":[130],"abilities":[131],"afforded":[132],"by":[133],"diversity":[135,154],"random":[137],"networks.":[139],"The":[140],"presented":[141],"results":[142],"open":[143],"up":[144],"interesting":[145],"future":[146],"research":[147],"directions,":[148],"such":[149],"as":[150],"combining":[151],"evolved":[152],"with":[155],"activity-dependent":[156],"plasticity.":[157]},"counts_by_year":[{"year":2024,"cited_by_count":2}],"updated_date":"2026-07-28T07:46:37.118299","created_date":"2025-10-10T00:00:00"}
