Searching for one-dimensional cellular automata in the absence of a priori information

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dc.contributor.authorOliveira G.M.B.
dc.contributor.authorde Oliveira P.P.B.
dc.contributor.authorOmar N.
dc.date.accessioned2024-03-13T01:46:59Z
dc.date.available2024-03-13T01:46:59Z
dc.date.issued2001
dc.description.abstract© Springer-Verlag Berlin Heidelberg 2001.Various investigations have been carried out on the computational power of cellular automata (CA), with concentrated efforts in the study of onedimensional CA. One of the approaches is the use of genetic algorithms (GA) to look for CA with a predefined computational behavior. We have previously shown a set of parameters that can be effective in helping forecast CA dynamic behavior; here, they are used as an heuristic to guide the GA search, by biasing selection, mutation and crossover, in the context of the Grouping Task (GT) for one-dimensional CA. Since GT is a new task, no a priori knowledge about its solutions is presently available; even then, the incorporation of the parameterbased heuristic entails a significant improvement over the results achieved by the plain genetic search.
dc.description.firstpage262
dc.description.lastpage271
dc.description.volume2159
dc.identifier.doi10.1007/3-540-44811-x_28
dc.identifier.issn1611-3349
dc.identifier.urihttps://dspace.mackenzie.br/handle/10899/38038
dc.relation.ispartofLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
dc.rightsAcesso Restrito
dc.titleSearching for one-dimensional cellular automata in the absence of a priori information
dc.typeArtigo de evento
local.scopus.citations2
local.scopus.eid2-s2.0-33645965630
local.scopus.subjectComputational power
local.scopus.subjectDynamic behaviors
local.scopus.subjectGenetic search
local.scopus.subjectPriori information
local.scopus.subjectPriori knowledge
local.scopus.updated2024-05-01
local.scopus.urlhttps://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=33645965630&origin=inward
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