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

Tipo
Artigo de evento
Data de publicação
2001
Periódico
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Citações (Scopus)
2
Autores
Oliveira G.M.B.
de Oliveira P.P.B.
Omar N.
Orientador
Título da Revista
ISSN da Revista
Título de Volume
Membros da banca
Programa
Resumo
© 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.
Descrição
Palavras-chave
Assuntos Scopus
Computational power , Dynamic behaviors , Genetic search , Priori information , Priori knowledge
Citação
DOI (Texto completo)