Explorando o uso de regras de correspondência condicional na busca evolutiva por autômatos celulares classificadores de densidade binária

dc.contributor.advisorOliveira, Pedro Paulo Balbi de
dc.contributor.advisor1Latteshttp://lattes.cnpq.br/9556738277476279por
dc.contributor.authorCardoso, Alberto Luis Libório
dc.creator.Latteshttp://lattes.cnpq.br/3828913742866942por
dc.date.accessioned2021-12-18T21:44:21Z
dc.date.available2021-12-18T21:44:21Z
dc.date.issued2020-12-08
dc.description.abstractCellular automata (CA) are discrete systems, fundamentally based upon local interactions, which, even though simple, may yield complex behaviour or universal computation. A classical problem to probe the computational capacity of CAs is the density classification task, whose objective is to decide the prevailing bit in an arbitrary binary sequence. Here we investigated the efficacy of a recent proposed representation of CA rules would have in that task, given that the new structure of the search space, induced by this new representation, might prove beneficial since new routes on that structure could lead to rules that perform well for such problem. Evolutionary searches using genetic algorithms were employed in different formulations of the density task, even in larger dimensionalities (more states) of the space, led to limited impact on the efficacy of the rules found. The results contrast with those found in the literature, pointing at limitations of the representation scheme employed applied to a density classification problem.eng
dc.description.sponsorshipCoordenação de Aperfeiçoamento de Pessoal de Nível Superiorpor
dc.formatapplication/pdf*
dc.identifier.citationCARDOSO, Alberto Luis Libório. Explorando o uso de regras de correspondência condicional na busca evolutiva por autômatos celulares classificadores de densidade binária. 2021.54 f. Dissertação( Engenharia Elétrica) - Universidade Presbiteriana Mackenzie, São Paulo.por
dc.identifier.urihttps://dspace.mackenzie.br/handle/10899/28603
dc.keywordscellular automataeng
dc.keywordsgenetic algorithmeng
dc.keywordsemergent computationeng
dc.keywordsartificial lifeeng
dc.keywordsdensity classification task.por
dc.languageporpor
dc.publisherUniversidade Presbiteriana Mackenziepor
dc.rightsAcesso Abertopor
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/
dc.subjectautômatos celularespor
dc.subjectalgoritmos genéticospor
dc.subjectcomputação emergentepor
dc.subjectvida artificialpor
dc.subjectdensity classification taskpor
dc.subject.cnpqCNPQ::ENGENHARIASpor
dc.titleExplorando o uso de regras de correspondência condicional na busca evolutiva por autômatos celulares classificadores de densidade bináriapor
dc.typeDissertaçãopor
local.contributor.board1Ruivo , Eurico Luiz Prospero
local.contributor.board1Latteshttp://lattes.cnpq.br/5918644808671007por
local.contributor.board2França, Fabricio Olivetti de
local.contributor.board2Latteshttp://lattes.cnpq.br/8788356220698686por
local.publisher.countryBrasilpor
local.publisher.departmentEscola de Engenharia Mackenzie (EE)por
local.publisher.initialsUPMpor
local.publisher.programEngenharia Elétricapor
Arquivos
Pacote Original
Agora exibindo 1 - 1 de 1
Carregando...
Imagem de Miniatura
Nome:
ALBERTO LUIS LIBORIO CARDOSO.pdf
Tamanho:
5.49 MB
Formato:
Adobe Portable Document Format
Descrição:
Alberto Luis Libório Cardoso
Licença do Pacote
Agora exibindo 1 - 1 de 1
Carregando...
Imagem de Miniatura
Nome:
license.txt
Tamanho:
2.06 KB
Formato:
Plain Text
Descrição: