Abstract
Most of the Evolutionary Algorithms handling variable-sized structures, like Genetic Programming, tend to produce too long solutions and the recombination operator used is often considered to be partly responsible of this phenomenon, called bloat. The Maximum Homologous Crossover (MHC) preserves similar structures from parents by aligning them according to their homology. This operator has already demonstrated interesting abilities in bloat reduction but also some weaknesses in the exploration of the size of programs during evolution. In this paper, we show that MHC do not induce any specific biases in the distribution of sizes, allowing size control during evolution. Two different methods for size control based on MHC are presented and tested on a symbolic regression problem. Results show that an accurate control of the size is possible while improving performances of MHC.
Preview
Unable to display preview. Download preview PDF.
Similar content being viewed by others
References
Altenberg, L.: The evolution of evolvability in genetic programming. In: Advances in Genetic Programming, MIT Press, Cambridge (1994)
Brameier, M., Bhanzhaf, W.: Explicit control of diversity and effective variation distance in linear genetic programming. In: Foster, J.A., Lutton, E., Miller, J., Ryan, C., Tettamanzi, A.G.B. (eds.) EuroGP 2002. LNCS, vol. 2278, pp. 37–49. Springer, Heidelberg (2002)
Bruce, W.S.: The lawnmower problem revisited: Stack-based genetic programming and automatically defined functions. In: Genetic Programming 1997: Proceedings of the Second Annual Conference, Stanford University, CA, USA, pp. 13–16. Morgan Kaufmann, San Francisco (1997)
Crawford-Marks, R., Spector, L.: Size control via size fair genetic operators in the PushGP genetic programming system. In: GECCO 2002: Proceedings of the Genetic and Evolutionary Computation Conference, 9-13 July 2002, pp. 733–739. Morgan Kaufmann, San Francisco (2002)
de Jong, E.D., Watson, R.A., Pollack, J.B.: Reducing bloat and promoting diversity using multi-objective methods. In: Proceedings of the Genetic and Evolutionary Computation Conference (GECCO-2001), pp. 11–18. Morgan Kaufmann, San Francisco (2001)
Defoin Platel, M., Clergue, M., Collard, P.: Homolgy gives size control in genetic porgramming. In: Proceedings of the 2003 Congress on Evolutionary Computation CEC 2003, pp. 281–288. IEEE Press, Los Alamitos (2003)
Defoin Platel, M., Clergue, M., Collard, P.: Maximum homologous crossover for linear genetic programming. In: Ryan, C., Soule, T., Keijzer, M., Tsang, E.P.K., Poli, R., Costa, E. (eds.) EuroGP 2003. LNCS, vol. 2610, pp. 194–203. Springer, Heidelberg (2003)
Langdon, W.B., Poli, R.: Fitness causes bloat. In: Second On-line World Conference on Soft Computing in Engineering Design and Manufacturing, pp. 13–22. Springer, Heidelberg (1997)
Luke, S.: Code growth is not caused by introns. In: Late Breaking Papers at the 2000 Genetic and Evolutionary Computation Conference, Las Vegas, Nevada, USA, vol. 8, pp. 228–235 (2000)
Luke, S.: Modification point depth and genome growth in genetic programming. Evol. Comput. 11(1), 67–106 (2003)
Perkis, T.: Stack-based genetic programming. In: Proceedings of the 1994 IEEE World Congress on Computational Intelligence, Orlando, Florida, USA, vol. 1, pp. 148–153. IEEE Press, Los Alamitos (1994)
Poli, R.: A simple but theoretically-motivated method to control bloat in genetic programming. In: Ryan, C., Soule, T., Keijzer, M., Tsang, E.P.K., Poli, R., Costa, E. (eds.) EuroGP 2003. LNCS, vol. 2610, pp. 204–214. Springer, Heidelberg (2003)
Poli, R., Langdon, W.B.: Genetic programming with one-point crossover. In: Soft Computing in Engineering Design and Manufacturing, June 23-27, 1997, pp. 180–189. Springer, London (1997)
Poli, R., McPhee, N.F.: Exact schema theorems for GP with one-point and standard crossover operating on linear structures and their application to the study of the evolution of size. In: Miller, J., Tomassini, M., Lanzi, P.L., Ryan, C., Tetamanzi, A.G.B., Langdon, W.B. (eds.) EuroGP 2001. LNCS, vol. 2038, pp. 126–142. Springer, Heidelberg (2001)
Rowe, J.E., McPhee, N.F.: The effects of crossover and mutation operators on variable length linear structures. In: Proceedings of the Genetic and Evolutionary Computation Conference (GECCO-2001), San Francisco, California, USA, July 7-11, 2001, pp. 535–542. Morgan Kaufmann, San Francisco (2001)
Soule, T., Foster, J.A.: An analysis of the causes of code growth in genetic programming. Genetic Programming and Evolvable Machines 3(1), 283–309 (2002)
Keller, R.E., Banzhaf, W., Nordin, P., Francone, F.D.: Genetic Programming - An Introduction. Morgan Kaufmann, San Francisco (1998)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2006 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Platel, M.D., Clergue, M., Collard, P. (2006). Size Control with Maximum Homologous Crossover. In: Talbi, EG., Liardet, P., Collet, P., Lutton, E., Schoenauer, M. (eds) Artificial Evolution. EA 2005. Lecture Notes in Computer Science, vol 3871. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11740698_2
Download citation
DOI: https://doi.org/10.1007/11740698_2
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-33589-4
Online ISBN: 978-3-540-33590-0
eBook Packages: Computer ScienceComputer Science (R0)