FILTER POSITION IN NETWORKS OF SUBSTITUTION PROCESSORS DOES NOT MATTER-Reference-Cited by-同舟云学术

FILTER POSITION IN NETWORKS OF SUBSTITUTION PROCESSORS DOES NOT MATTER

Published:2011-01 Issue:01 Volume:22 Page:155-165
ISSN:0129-0541
Container-title:International Journal of Foundations of Computer Science
language:en
Short-container-title:Int. J. Found. Comput. Sci.

Author:

MONTORO FERNANDO ARROYO¹,CASTELLANOS JUAN²,MITRANA VICTOR³⁴,SANTOS EUGENIO³,SEMPERE JOSE M.⁵

Affiliation:

1. Depto. Lenguajes, Proyectos y Sistemas Informticos, Escuela Universitaria de Informtica, Universidad Politcnica de Madrid, Ctra. de Valencia Km. 7, 28031 Madrid, Spain

2. Department of Artificial Intelligence, Polytechnical University of Madrid, 28660 Boadilla del Monte, Madrid, Spain

3. Depto. Organización y Estructura de la Información, Escuela Universitaria de Informática, Universidad Politécnica de Madrid, Crta. de Valencia km. 7 - 28031 Madrid, Spain

4. Faculty of Mathematics and Computer Science, University of Bucharest, Str. Academiei 14, 010014, Bucharest, Romania

5. Department of Information Systems and Computation, Technical University of Valencia, Camino de Vera s/n. 46022 Valencia, Spain

Abstract

It is known ([4]) that moving the filters from the nodes to the edges in accepting hybrid networks of evolutionary processors does not decrease the computational power of the model which equals that of a Turing machine. A direct and time complexity preserving simulation is presented in [1]. All three types of processors (substitution, insertion, deletion) are essentially used in this simulation. In this note we prove that such a direct simulation between networks containing substitution nodes only still exists.

Publisher

World Scientific Pub Co Pte Lt

Subject

Computer Science (miscellaneous)

Link

https://www.worldscientific.com/doi/pdf/10.1142/S0129054111007915

Reference9 articles.

1. Networks of parallel language processors

2. Evolutionary systems: a language generating device inspired by evolving communities of cells

3. L. Errico and C. Jesshope, Artificial Intelligence and Information-Control Systems of Robots 94 (World Scientific, 1994) pp. 31–40.

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