Evolving sequential combinations of elementary cellular automata rules

dc.contributor.authorMartins C.L.M.
dc.contributor.authorDe Oliveira P.P.B.
dc.date.accessioned2024-03-13T01:43:34Z
dc.date.available2024-03-13T01:43:34Z
dc.date.issued2005
dc.description.abstractPerforming computations with cellular automata, individually or arranged in space or time, opens up new conceptual issues in emergent, artificial life type forms of computation, and opens up the possibility of novel technological advances. Here, a methodology for combining sequences of elementary cellular automata is presented, in order to perform a given computation. The problem at study is the well-known density classification task that consists of determining the most frequent bit in a binary string. The methodology relies on an evolutionary algorithm, together with analyses driven by background knowledge on dynamical behaviour of the rules and their parametric estimates, as well as those associated with the formal behaviour characterisation of the rules involved. The resulting methodology builds upon a previous approach available in the literature, and shows its efficacy by leading to 2 rule combinations already known, and to additional 26, apparently unknown so far. © Springer-Verlag Berlin Heidelberg 2005.
dc.description.firstpage461
dc.description.lastpage470
dc.description.volume3630 LNAI
dc.identifier.doi10.1007/11553090_47
dc.identifier.issn0302-9743
dc.identifier.urihttps://dspace.mackenzie.br/handle/10899/37849
dc.relation.ispartofLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
dc.rightsAcesso Restrito
dc.titleEvolving sequential combinations of elementary cellular automata rules
dc.typeArtigo de evento
local.scopus.citations16
local.scopus.eid2-s2.0-33645990270
local.scopus.subjectArtificial life type forms
local.scopus.subjectElementary cellular automata rules
local.scopus.subjectSequential combinations
local.scopus.subjectTechnological advances
local.scopus.updated2024-05-01
local.scopus.urlhttps://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=33645990270&origin=inward
Arquivos