Abstract
This study attempts to decompose the behaviour of mutation in Grammatical Evolution (GE). Standard GE mutation can be divided into two types of events, those that are structural in nature and those that are nodal. A structural event can alter the length of the phenotype whereas a nodal event simply alters the value at any terminal (leaf or internal node) of a derivation tree. We analyse the behaviour of standard mutation and compare it to the behaviour of its nodal and structural components. These results are then compared with standard GP operators to see how they differ. This study increases our understanding of how the search operators of an evolutionary algorithm behave.
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
Poli, R., McPhee, N.F., Langdon, W.B.: A Field Guide to Genetic Programming (2008), http://lulu.com , http://www.gp-field-guide.org.uk
O’Neill, M., Ryan, C.: Grammatical Evolution: Evolutionary Automatic Programming in an Arbitrary Language. Kluwer Academic Publishers, Dordrecht (2003)
O’Neill, M., Ryan, C., Keijzer, M., Cattolico, M.: Crossover in Grammatical Evolution. Genetic Programming and Evolvable Machines 4(1), 67–93 (2003)
Harper, R., Blair, A.: A Structure Preserving Crossover in Grammatical Evolution. In: Proc. CEC 2005 IEEE Congress on Evolutionary Computation, vol. 3, pp. 2537–2544. IEEE Press, Los Alamitos (2005)
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)
Langdon, W.B., Poli, R.: An Analysis of the MAX Problem in Genetic Programming. In: Proceedings of the second annual conference, Stanford University, July 13-16, pp. 222–230. Morgan Kaufmann Pub., San Francisco (1997)
Langdon, W.B., Poli, R.: An analysis of the MAX problem in genetic programming. Genetic Programming, 222–230 (1997) (Citeseer)
Hugosson, J., Hemberg, E., Brabazon, A., O’Neill, M.: An investigation of the mutation operator using different representations in Grammatical Evolution. In: Proc. 2nd International Symposium Advances in Artificial Intelligence and Applications, vol. 2, pp. 409–419 (2007)
Koza, J.R.: Genetic programming: on the programming of computers by means of natural selection. The MIT press, Cambridge (1992)
Dempsey, I., O‘Neill, M., Brabazon, A.: Foundations in Grammatical Evolution for Dynamic Environments. Springer, Heidelberg (2009)
Byrne, J., O’Neill, M., Brabazon, A.: Structural and nodal mutation in grammatical evolution. In: Proceedings of the 11th Annual conference on Genetic and evolutionary computation, pp. 1881–1882. ACM, New York (2009)
O’Neill, M., Hemberg, E., Gilligan, C., Bartley, E., McDermott, J., Brabazon, A.: GEVA - Grammatical Evolution in Java (v1.0). UCD School of Computer Science Technical Report UCD-CSI-2008-09 (2008), http://ncra.ucd.ie/geva/
O’Neill, M., Hemberg, E., Gilligan, C., Bartley, E., McDermott, J., Brabazon, A.: GEVA: Grammatical Evolution in Java. SIGEVOlution 3(2), 17–22 (2009)
Keijzer, M., Ryan, C., O’Neill, M., Cattolico, M., Babovic, V.: Ripple crossover in genetic programming. In: Miller, J., Tomassini, M., Lanzi, P.L., Ryan, C., Tetamanzi, A.G.B., Langdon, W.B. (eds.) EuroGP 2001. LNCS, vol. 2038, pp. 74–86. Springer, Heidelberg (2001)
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
Byrne, J., O’Neill, M., McDermott, J., Brabazon, A. (2010). An Analysis of the Behaviour of 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_2
Download citation
DOI: https://doi.org/10.1007/978-3-642-12148-7_2
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)