Dynamic behaviour forecast as a driving force in the coevolution of one-dimensional cellular automata

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dc.contributor.authorOliveira G.M.B.
dc.contributor.authorAsakura O.K.N.
dc.contributor.authorDe Oliveira P.P.B.
dc.date.accessioned2024-03-13T01:46:32Z
dc.date.available2024-03-13T01:46:32Z
dc.date.issued2002
dc.description.abstract© 2002 IEEE.Various evolutionary methods have been used to look for cellular automata (CA) with a predefined computational behaviour. The most widely studied CA task is the density classification task (DCT) and the best rule currently known for it was obtained by a coevolutionary genetic algorithm (CGA). Here, we analyse the influence of incorporating a parameter-based heuristic into the coevolutionary search. The results obtained show that the parameters can effectively help a CGA in searching for DCT rules, and suggest that the choice of the amount of bias in the search, allowed for the heuristic, is more sensitive than in previous uses we made of it within standard evolutionary algorithms.
dc.description.firstpage98
dc.description.lastpage103
dc.description.volume2002-January
dc.identifier.doi10.1109/SBRN.2002.1181442
dc.identifier.issn1522-4899
dc.identifier.urihttps://dspace.mackenzie.br/handle/10899/38013
dc.relation.ispartofProceedings - Brazilian Symposium on Neural Networks, SBRN
dc.rightsAcesso Restrito
dc.subject.otherlanguageAlgorithm design and analysis
dc.subject.otherlanguageBiology computing
dc.subject.otherlanguageConcurrent computing
dc.subject.otherlanguageDiscrete cosine transforms
dc.subject.otherlanguageEvolution (biology)
dc.subject.otherlanguageEvolutionary computation
dc.subject.otherlanguageGenetic algorithms
dc.subject.otherlanguageHigh performance computing
dc.subject.otherlanguageParallel processing
dc.subject.otherlanguageSearch methods
dc.titleDynamic behaviour forecast as a driving force in the coevolution of one-dimensional cellular automata
dc.typeArtigo de evento
local.scopus.citations1
local.scopus.eid2-s2.0-70649098598
local.scopus.subjectAlgorithm design and analysis
local.scopus.subjectBiology computing
local.scopus.subjectConcurrent computing
local.scopus.subjectEvolution biology
local.scopus.subjectHigh performance computing
local.scopus.subjectParallel processing
local.scopus.subjectSearch method
local.scopus.updated2024-05-01
local.scopus.urlhttps://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=70649098598&origin=inward
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