Abstract
An often-mentioned issue with Grammatical Evolution is that a small change in the genotype, through mutation or crossover, may completely change the meaning of all of the following genes. This paper analyses the crossover and mutation operations in GE, in particular examining the constructive or destructive nature of these operations when occurring at points throughout a genotype. The results we present show some strong support for the idea that events occurring at the first positions of a genotype are indeed more destructive, but also indicate that they may be the most constructive crossover and mutation points too. We also demonstrate the sensitivity of this work to the precise definition of what is constructive/destructive.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
McKay, R.I., Nguyen, X.H., Whigham, P.A., Shan, Y.: Grammars in genetic programming: A brief review. In: Kang, L., Cai, Z., Yan, Y. (eds.) Progress in Intelligence Computation and Intelligence: Proceedings of the International Symposium on Intelligence, Computation and Applications, Wuhan, PRC, China, pp. 3–18. University of Geosciences Press (2005)
O’Neill, M., Ryan, C.: Grammatical evolution. IEEE Transactions on Evolutionary Computation 5, 349–358 (2001)
Rothlauf, F., Oetzel, M.: On the locality of grammatical evolution. In: Collet, P., Tomassini, M., Ebner, M., Gustafson, S., Ekárt, A. (eds.) EuroGP 2006. LNCS, vol. 3905, pp. 320–330. Springer, Heidelberg (2006)
Koza, J.R.: Genetic Programming: On the Programming of Computers by Means of Natural Selection. MIT Press, Cambridge (1992)
Nordin, P., Francone, F., Banzhaf, W.: Explicitly defined introns and destructive crossover in genetic programming. In: Rosca, J.P. (ed.) Proceedings of the Workshop on Genetic Programming: From Theory to Real-World Applications, Tahoe City, California, USA, pp. 6–22 (1995)
Johnson, C.: Genetic programming crossover: Does it cross over? In: Vanneschi, L., Gustafson, S., Moraglio, A., De Falco, I., Ebner, M. (eds.) EuroGP 2009. LNCS, vol. 5481, pp. 97–108. Springer, Heidelberg (2009)
Nordin, P., Banzhaf, W.: Complexity compression and evolution. In: Eshelman, L. (ed.) Genetic Algorithms: Proceedings of the Sixth International Conference (ICGA 1995), Pittsburgh, PA, USA, pp. 310–317. Morgan Kaufmann, San Francisco (1995)
Teller, A., Veloso, M.: PADO: A new learning architecture for object recognition. In: Ikeuchi, K., Veloso, M. (eds.) Symbolic Visual Learning, pp. 81–116. Oxford University Press, Oxford (1996)
Harper, R., Blair, A.: A self-selecting crossover operator. In: Yen, G.G., et al. (eds.) Proceedings of the 2006 IEEE Congress on Evolutionary Computation, Vancouver, pp. 5569–5576. IEEE Press, Los Alamitos (2006)
Harper, R., Blair, A.: A structure preserving crossover in grammatical evolution. In: Corne, D., et al. (eds.) Proceedings of the 2005 IEEE Congress on Evolutionary Computation, Edinburgh, UK, vol. 3, pp. 2537–2544. IEEE Press, Los Alamitos (2005)
Keijzer, M., Ryan, C., O’Neill, M., Cattolico, M., Babovic, V.: Ripple crossover in genetic programming. In: Miller, J.F., Tomassini, M., Lanzi, P.L., Ryan, C., Tettamanzi, A.G.B., Langdon, W.B. (eds.) EuroGP 2001. LNCS, vol. 2038, pp. 74–86. Springer, Heidelberg (2001)
O’Neill, M., Ryan, C.: Crossover in grammatical evolution: A smooth operator? In: Poli, R., Banzhaf, W., Langdon, W.B., Miller, J.F., Nordin, P., Fogarty, T.C. (eds.) EuroGP 2000. LNCS, vol. 1802, pp. 149–162. Springer, Heidelberg (2000)
Hugosson, J., Hemberg, E., Brabazon, A., O’Neill, M.: An investigation of the mutation operator using different representations in grammatical evolution. In: 2nd International Symposium Advances in Artificial Intelligence and Applications, Wisla, Poland, vol. 2, pp. 409–419 (2007)
Tackett, W.A.: Greedy recombination and genetic search on the space of computer programs. In: Whitley, L.D., Vose, M.D. (eds.) Foundations of Genetic Algorithms, Estes Park, Colorado, USA, 1994, vol. 3, pp. 271–297. Morgan Kaufmann, San Francisco (1994)
Nielson, F., Nielson, H.R., Hankin, C.: Principles of Program Analysis. Springer, Heidelberg (1999)
Majeed, H., Ryan, C.: Using context-aware crossover to improve the performance of GP. In: Keijzer, M., et al. (eds.) GECCO 2006: Proceedings of the 8th annual conference on Genetic and evolutionary computation, Seattle, Washington, USA, vol. 1, pp. 847–854. ACM Press, New York (2006)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2010 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Castle, T., Johnson, C.G. (2010). Positional Effect of Crossover and Mutation in Grammatical Evolution. In: Esparcia-Alcázar, A.I., Ekárt, A., Silva, S., Dignum, S., Uyar, A.Ş. (eds) Genetic Programming. EuroGP 2010. Lecture Notes in Computer Science, vol 6021. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-12148-7_3
Download citation
DOI: https://doi.org/10.1007/978-3-642-12148-7_3
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-12147-0
Online ISBN: 978-3-642-12148-7
eBook Packages: Computer ScienceComputer Science (R0)