Skip to main content

Evolving Constructors for Infinitely Growing Sorting Networks and Medians

  • Conference paper
SOFSEM 2004: Theory and Practice of Computer Science (SOFSEM 2004)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 2932))

Abstract

An approach is presented in which the object under design can grow continually and infinitely. First, a small object (that we call the embryo) has to be prepared to solve the trivial instance of a problem. Then the evolved program (the constructor) is applied on the embryo to create a larger object (solving a larger instance of the problem). Then the same constructor is used to create a new instance of the object from the created larger object and so on. Every new instance of the object is able to perform the function of all previous instances. As an example, constructors for growing sorting and median networks are evolved and analyzed.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 39.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 54.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Bentley, P.: Evolutionary Design By Computers. Morgan Kaufmann Publishers, San Francisco (1999)

    MATH  Google Scholar 

  2. Boers, E.J.W., Kuiper, H.: Biological Metaphors and the Design of Artificial Neural Networks. Master Thesis, Departments of Computer Science and Experimental and Theoretical Psychology, Leiden University (1992)

    Google Scholar 

  3. Choi, S.S., Moon, B.R.: More Effective Genetic Search for the Sorting Network Problem. In: Proc. of the Genetic and Evolutionary Computation Conference GECCO 2002, pp. 335–342. Morgan Kaufmann, San Francisco (2002)

    Google Scholar 

  4. Devillard, N.: Fast Median Search: An ANSI C Implementation. (1998), http://ndevilla.free.fr/median/median/index.html

  5. de Garis, H., et al.: ATR’s Artificial Brain (CAM-Brain) Project: A Sample of What Individual “CoDi-1 Bit” Model Evolved Neural Net Modules Can Do With Digital and Analog I/O. In: Proc. of the 1st NASA/DoD Workshop on Evolvable Hardware, pp. 102–110. IEEE CS Press, Los Alamitos (1999)

    Chapter  Google Scholar 

  6. Gordon, T.G.W., Bentley, P.: Towards Development in Evolvable Hardware. In: Proc. of the 2002 NASA/DoD Conference on Evolvable Hardware, pp. 241–250. IEEE CS Press, Los Alamitos (2002)

    Chapter  Google Scholar 

  7. Haddow, P., Tufte, G., van Remortel, P.: Shrinking the Genotype: L-systems for EHW? In: Liu, Y., Tanaka, K., Iwata, M., Higuchi, T., Yasunaga, M. (eds.) ICES 2001. LNCS, vol. 2210, pp. 128–139. Springer, Heidelberg (2001)

    Chapter  Google Scholar 

  8. Hillis, W.D.: Co-Evolving Parasites Improve Simulated Evolution as an Optimization Procedure. Physica D42, 228–234 (1990)

    Google Scholar 

  9. Hornby, G.S., Pollack, J.B.: The Advantages of Generative Grammatical Encodings for Physical Design. In: Proc. of the 2001 Congress on Evolutionary Computation CEC 2001, pp. 600–607. IEEE CS Press, Los Alamitos (2001)

    Chapter  Google Scholar 

  10. Huelsbergen, L.: Finding General Solutions to the Parity Problem by Evolving Machine-Language Representations. In: Proc. of Conf. on Genetic Programming, pp. 158–166 (1998)

    Google Scholar 

  11. Imamura, K., Foster, J.A., Krings, A.W.: The Test Vector Problem and Limitations to Evolving Digital Circuits. In: Proc. of the 2nd NASA/DoD Workshop on Evolvable Hardware, pp. 75–79. IEEE CS Press, Los Alamitos (2000)

    Chapter  Google Scholar 

  12. Juillé, H.: Evolution of Non-Deterministic Incremental Algorithms as a New Approach for Search in State Spaces. In: Proc. of 6th Int. Conf. on Genetic Algorithms, pp. 351–358. Morgan Kaufmann, San Francisco (1995)

    Google Scholar 

  13. Kitano, H.: Morphogenesis for Evolvable Systems. In: Sanchez, E., Tomassini, M. (eds.) Towards Evolvable Hardware 1995. LNCS, vol. 1062, pp. 99–117. Springer, Heidelberg (1996)

    Google Scholar 

  14. Knuth, D.E.: The Art of Computer Programming: Sorting and Searching, 2nd edn. Addison Wesley, Reading (1998)

    Google Scholar 

  15. Kolte, P., Smith, R., Su, W.: A Fast Median Filter Using AltiVec. In: Proc. of the IEEE Conf. on Computer Design, Austin, Texas, pp. 384–391. IEEE CS Press, Los Alamitos (1999)

    Google Scholar 

  16. Koza, J.R., Bennett III., F.H., Andre, D., Keane, M.A.: Genetic Programming III: Darwinian Invention and Problem Solving. Morgan Kaufmann, San Francisco (1999)

    MATH  Google Scholar 

  17. Miller, J., Job, D., Vassilev, V.: Principles in the Evolutionary Design of Digital Circuits – Part II. Genetic Programming and Evolvable Machines 1(2), 259–288 (2000)

    Article  MATH  Google Scholar 

  18. Miller, J., Thomson, P.: A Developmental Method for Growing Graphs and Circuits. In: Tyrrell, A.M., Haddow, P.C., Torresen, J. (eds.) ICES 2003. LNCS, vol. 2606, pp. 93–104. Springer, Heidelberg (2003)

    Chapter  Google Scholar 

  19. Sekanina, L.: Evolvable Components: From Theory to Hardware Implementations. Natural Computing Series. Springer, Heidelberg (2003)

    Google Scholar 

  20. Streeter, M.J., Keane, M.A., Koza, J.R.: Routine Duplication of Post-2000 Patented Inventions by Means of Genetic Programming. In: Foster, J.A., Lutton, E., Miller, J., Ryan, C., Tettamanzi, A.G.B. (eds.) EuroGP 2002. LNCS, vol. 2278, pp. 26–36. Springer, Heidelberg (2002)

    Chapter  Google Scholar 

  21. Tempesti, G., et al.: Ontogenetic Development and Fault Tolerance in the POEtic Tissue. In: Tyrrell, A.M., Haddow, P.C., Torresen, J. (eds.) ICES 2003. LNCS, vol. 2606, pp. 141–152. Springer, Heidelberg (2003)

    Chapter  Google Scholar 

  22. Zeno, R.: A Reference of the Best-Known Sorting Networks for up to 16 Inputs (2003), http://www.angelfire.com/blog/ronz/

Download references

Author information

Authors and Affiliations

Authors

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2004 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Sekanina, L. (2004). Evolving Constructors for Infinitely Growing Sorting Networks and Medians. In: Van Emde Boas, P., Pokorný, J., Bieliková, M., Štuller, J. (eds) SOFSEM 2004: Theory and Practice of Computer Science. SOFSEM 2004. Lecture Notes in Computer Science, vol 2932. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-24618-3_27

Download citation

  • DOI: https://doi.org/10.1007/978-3-540-24618-3_27

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-20779-5

  • Online ISBN: 978-3-540-24618-3

  • eBook Packages: Springer Book Archive

Publish with us

Policies and ethics