Abstract
In this work we present a way to find the set of rules for the evolution of a one-dimensional cellular automata through its window of evolution using genetic algorithm, a search routine that mimics the behavior of the genetic evolution of living beings. As a result, we present the rules obtained by this strategy to the windows of the development of elementary automata rule 110 presented by Stephen Wolfram.
This is a preview of subscription content, log in via an institution.
Buying options
Tax calculation will be finalised at checkout
Purchases are for personal use only
Learn about institutional subscriptionsPreview
Unable to display preview. Download preview PDF.
References
Hedlund, G.A.: Endomorphisms and automorphisms of the shift dynamical system. Theory of Computing Systems 3(4), 320–375 (1969)
Gardner, M.: Mathematical games: The fantastic combinations of John Conway’s new solitaire game life. Scientific American 223, 120–123 (1970)
IGBLAN: Life universal computer, http://www.igblan.free-online.co.uk/igblan/ca
Zuse, K.: Calculating Space. Project MAC Report, MIT Technical Translation (1970)
Wolfram, S.: Statistical mechanics of cellular automata. Reviews of Modern Physics 55, 601–644 (1983)
Wolfram, S.: A new kind of science. Wolfram Media, Illinois (2002)
Dürr, C., Rapaport, I., Theyssier, G.: Cellular automata and communication complexity. Theoretical Computer Science 322(2), 355–368 (2004)
Dantchev, S.: Dynamic neighbourhood cellular automata. The Computer Journal 54(1), 26–30 (2011)
Sahu, S., Oono, H., Ghosh, S., Bandyopadhyay, A., Fujita, D., Peper, F., Isokawa, T., Pati, R.: On cellular automata rules of molecular arrays. Natural Computing 11(2), 311–321 (2012)
Vanneschi, L., Mauri, G.: A study on learning robustness using asynchronous 1D cellular automata rules. Natural Computing 11(2), 289–302 (2012)
Maji, P., Shaw, C., Ganguly, N., Sikdar, B.K., Pal Chaudhuri, P.: Theory and Application of Cellular Automata For Pattern Classification. Fundamenta Informaticae 58(3-4), 321–354 (2003)
Mitchell, M., Crutchfield, J.P., Das, R.: Evolving cellular automata with genetic algorithms: A review of recent works. In: Proceedings of the First International Conference on Evolutionary Computation and Its Applications (EvCA 1996). Russian Academy of Sciences, Moscow (1996)
Koumousis, V.K., Katsara, C.P.: A saw-tooth genetic algorithm combining the effects of variable population size and reinitialization to enhance performance. IEEE Transaction on Evolutionary Computation 10(1), 19–28 (2006)
Koljonen, J., Alander, J.T.: Effects of population size and relative elitism on optimization speed and reliability of genetic algorithms. In: Proceedings of the 9th Scandinavian Conference on Artificial Intelligence, pp. 25–27 (2006)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2012 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Júnior, E.L.S., Ferreira, T.A.E., da Silva, M.G. (2012). Discovering the Rules of a Elementary One-Dimensional Automaton. In: Yin, H., Costa, J.A.F., Barreto, G. (eds) Intelligent Data Engineering and Automated Learning - IDEAL 2012. IDEAL 2012. Lecture Notes in Computer Science, vol 7435. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-32639-4_38
Download citation
DOI: https://doi.org/10.1007/978-3-642-32639-4_38
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-32638-7
Online ISBN: 978-3-642-32639-4
eBook Packages: Computer ScienceComputer Science (R0)