Advertisement

Hybrid Networks of Evolutionary Processors

  • Carlos Martín-Vide
  • Victor Mitrana
  • Mario J. Pérez-Jiménez
  • Fernando Sancho-Caparrini
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 2723)

Abstract

A hybrid network of evolutionary processors consists of several processors which are placed in nodes of a virtual graph and can perform one simple operation only on the words existing in that node in accordance with some strategies. Then the words which can pass the output filter of each node navigate simultaneously through the network and enter those nodes whose input filter was passed. We prove that these networks with filters defined by simple random-context conditions, used as language generating devices, are able to generate all linear languages in a very efficient way, as well as non-context-free languages. Then, when using them as computing devices, we present two linear solutions of the Common Algorithmic Problem.

Keywords

Output Node Regular Language Mathematical Linguistics Hybrid Network Underlying Graph 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    Castellanos, J., Martín-Vide, C., Mitrana, V., Sempere, J.: Solving NP-complete problems with networks of evolutionary processors. IWANN 2001 (J. Mira, A. Prieto, eds.), LNCS 2084, Springer-Verlag (2001) 621–628.Google Scholar
  2. 2.
    Castellanos, J., Martín-Vide, C., Mitrana, V., Sempere, J.: Networks of evolutionary processors. Submitted (2002).Google Scholar
  3. 3.
    Csuhaj-Varjú, E., Dassow, J., Kelemen, J., Păun, G.: Grammar Systems, Gordon and Breach, 1993.Google Scholar
  4. 4.
    Csuhaj-Varjú, E., Salomaa, A.: Networks of parallel language processors. New Trends in Formal Languages (Gh. Păun, A. Salomaa, eds.), LNCS 1218, Springer Verlag (1997) 299–318.Google Scholar
  5. 5.
    Csuhaj-Varjú, E., Mitrana, V.: Evolutionary systems: a language generating device inspired by evolving communities of cells. Acta Informatica 36 (2000) 913–926.zbMATHCrossRefMathSciNetGoogle Scholar
  6. 6.
    Errico, L., Jesshope, C.: Towards a new architecture for symbolic processing. Artificial Intelligence and Information-Control Systems of Robots’ 94 (I. Plander, ed.), World Sci. Publ., Singapore (1994) 31–40.Google Scholar
  7. 7.
    Fahlman, S.E., Hinton, G.E., Seijnowski, T.J.: Massively parallel architectures for AI: NETL, THISTLE and Boltzmann machines. Proc. AAAI National Conf. on AI, William Kaufman, Los Altos (1983) 109–113.Google Scholar
  8. 8.
    Garey, M., Johnson, D.: Computers and Intractability. A Guide to the Theory of NP-completeness, Freeman, San Francisco, CA, 1979.zbMATHGoogle Scholar
  9. 9.
    Head, T., Yamamura, M., Gal, S.: Aqueous computing: writing on molecules. Proc. of the Congress on Evolutionary Computation 1999, IEEE Service Center, Piscataway, NJ (1999) 1006–1010.CrossRefGoogle Scholar
  10. 10.
    Kari, L.: On Insertion and Deletion in Formal Languages, Ph.D. Thesis, University of Turku, 1991.Google Scholar
  11. 11.
    Kari, L., Păun, G., Thierrin, G., Yu, S.: At the crossroads of DNA computing and formal languages: Characterizing RE using insertion-deletion systems. Proc. 3rd DIMACS Workshop on DNA Based Computing, Philadelphia (1997) 318–333.Google Scholar
  12. 12.
    Kari, L., Thierrin, G.: Contextual insertion/deletion and computability. Information and Computation 131 (1996) 47–61.zbMATHCrossRefMathSciNetGoogle Scholar
  13. 13.
    Hillis, W.D.: The Connection Machine, MIT Press, Cambridge, 1985.Google Scholar
  14. 14.
    Martín-Vide, C., Păun, G., Salomaa, A.: Characterizations of recursively enumerable languages by means of insertion grammars. Theoretical Computer Science 205 (1998) 195–205.zbMATHCrossRefMathSciNetGoogle Scholar
  15. 15.
    Martín-Vide, Mitrana, V., Păun, G.: On the power of valuations in P systems. Computacion y Sistemas 5 (2001) 120–128.Google Scholar
  16. 16.
    Păun, G.: Computing with membranes. J. Comput. Syst. Sci. 61(2000) 108–143.CrossRefzbMATHGoogle Scholar
  17. 17.
    Sankoff, D. et al.: Gene order comparisons for phylogenetic inference: Evolution of the mitochondrial genome. Proc. Natl. Acad. Sci. USA 89 (1992) 6575–6579.CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2003

Authors and Affiliations

  • Carlos Martín-Vide
    • 1
  • Victor Mitrana
    • 2
  • Mario J. Pérez-Jiménez
    • 3
  • Fernando Sancho-Caparrini
    • 3
  1. 1.Research Group in Mathematical LinguisticsRovira i Virgili UniversityTarragonaSpain
  2. 2.Faculty of Mathematics and Computer ScienceUniversity of BucharestBucharestRomania
  3. 3.Department of Computer Science and Artificial IntelligenceUniversity of SevilleSpain

Personalised recommendations