No Coercion and No Prohibition, a Position Independent Encoding Scheme for Evolutionary Algorithms – The Chorus System

  • Conor Ryan
  • Atif Azad
  • Alan Sheahan
  • Michael O’Neill
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 2278)


We describe a new encoding system, Chorus, for grammar based Evolutionary Algorithms. This scheme is coarsely based on the manner in nature in which genes produce proteins that regulate the metabolic pathways of the cell. The phenotype is the behaviour of the cells metabolism, which corresponds to the development of the computer program in our case. In this procedure, the actual protein encoded by a gene is the same regardless of the position of the gene within the genome.

We show that the Chorus system has a very convenient Regular Expression – type schema notation that can be used to describe the presence of various phenotypes or phenotypic traits. This schema notation is used to demonstrate that massive areas of neutrality can exist in the search landscape, and the system is also shown to be able to dispense with large areas of the search space that are unlikely to contain useful solutions.


Regular Expression Production Rule Schema Notation Symbolic Regression Grammatical Evolution 
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.


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. 1.
    J.J. Freeman, “A Linear Representation for GP using Context Free Grammars” in Genetic Programming 1998: Proc. 3rd Annu. Conf., J.R. Koza, W. Banzhaf, K. Chellapilla, K. Deb, M. Dorigo, D.B. Fogel, M.H. Garzon, D.E. Goldberg, H. Iba, R.L. Riolo, Eds. Madison, Wisconsin: MIT Press, 1998, pp. 72–77.Google Scholar
  2. 2.
    H. Horner, A C++ class library for Genetic Programming: The Vienna University of Economics Genetic Programming Kernel. Release 1.0, Operating instruction. Vienna University of Economics, 1996.Google Scholar
  3. 3.
    R. Keller and W. Banzhaf, “GP using mutation, reproduction and genotype-phenotype mapping from linear binary genomes into linear LALR phenotypes” in Genetic Programming 1996: Proc. 1st Annu. Conf., J.R. Koza, D.E. Goldberg, D.B. Fogel, and R.L. Riolo, Eds. Stanford, CA: MIT Press 1996, pp. 116–122.Google Scholar
  4. 4.
    O’Neill M., Ryan C. Grammatical Evolution. IEEE Transactions on Evolutionary Computation. 2001.Google Scholar
  5. 5.
    N. Paterson and M. Livesey, “Evolving caching algorithms in C by GP” in Genetic Programming 1997: Proc. 2nd Annu. Conf., MIT Press, 1997, pp. 262–267. MIT Press.Google Scholar
  6. 6.
    C. Ryan, J.J. Collins and M. O’Neill, “Grammatical Evolution: Evolving Programs for an Arbitrary Language”, in EuroGP’98: Proc. of the First EuropeanWorkshop on Genetic Programming (Lecture Notes in Computer Science 1391), Paris, France: Springer 1998, pp. 83–95.Google Scholar
  7. 7.
    P. Whigham, “Grammatically-based Genetic Programming” in Proceedings of theWorkshop on GP: From Theory to Real-World Applications, Morgan Kaufmann, 1995, pp. 33–41.Google Scholar
  8. 8.
    J. Koza. “Genetic Programming”. MIT Press, 1992.Google Scholar
  9. 9.
    Goldberg D E, Korb B, Deb K. Messy genetic algorithms: motivation, analysis, and first results. Complex Syst. 3Google Scholar
  10. 10.
    Gruau, F. 1994. Neural Network synthesis using cellular encoding and the genetic algorithm. PhD Thesis from Centre d’etude nucham, P. 1995. Inductive bias and genetic programming. In First International Conference on Genetic Algorithms in Engineering Systems: Innovations and Applications, pages 461–466. UK:IEE.Google Scholar
  11. 11.
    Lewin B. Genes VII. Oxford University Press, 1999.Google Scholar
  12. 12.
    Wong, M. and Leung, K. 1995. Applying logic grammars to induce subfunctions in genetic prorgramming. In Proceedings of the 1995 IEEE conference on Evolutionary Computation, pages 737–740. USA:IEEE Press.Google Scholar
  13. 13.
    Zubay G. Biochemistry. Wm. C. Brown Publishers, 1993Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2002

Authors and Affiliations

  • Conor Ryan
    • 1
  • Atif Azad
    • 1
  • Alan Sheahan
    • 1
  • Michael O’Neill
    • 1
  1. 1.Department of Computer Science and Information SystemsUniversity of LimerickIreland

Personalised recommendations