Abstract
We introduce a new recombination operator, the Maximum Homologous Crossover for Linear Genetic Programming. In contrast to standard crossover, it attempts to preserve similar structures from parents, by aligning them according to their homology, thanks to an algorithm used in Bio-Informatics. To highlight disruptive effects of crossover operators, we introduce the Royal Road landscapes and the Homology Driven Fitness problem, for Linear Genetic Programming. Two variants of the new crossover operator are described and tested on this landscapes. Results show a reduction in the bloat phenomenon and in the frequency of deleterious crossovers.
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
Lee Altenberg. The evolution of evolvability in genetic programming. In Advances in Genetic Programming. MIT Press, 1994.
P. J. Angeline. Subtree crossover: Building block engine or macromutation ? In Genetic Programming 1997: Proceedings of the Second Annual Conference. Morgan Kaufmann, July 1997.
Markus Brameier and Wolfgang Banzhaf. A comparison of linear genetic programming and neural networks in medical data mining. IEEE Transactions on Evolutionary Computation, 5(1):17–26, 2001.
Markus Brameier and Wolfgang Bhanzhaf. Explicit control of diversity and effective variation distance in linear genetic programming, 2001.
Manuel Clergue, Philippe Collard, Marco Tomassini, and Leonardo Vanneschi. Fitness distance correlation and problem difficulty for genetic programming. In GECCO 2002: Proceedings of the Genetic and Evolutionary Computation Conference, pages 724–732, New York, 9–13 July 2002. Morgan Kaufmann Publishers.
Patrik D’haeseleer. Context preserving crossover in genetic programming. In Proceedings of the 1994 IEEE World Congress on Computational Intelligence, volume 1, pages 256–261, Orlando, Florida, USA, 27–29 1994. IEEE Press.
Stephanie Forrest and Melanie Mitchell. Relative building-block fitness and the building-block hypothesis. In Foundation of Genetic Algorithms 2, pages 109–126. Morgan Kaufman, 1993.
D. Gusfield. Algorithms on Strings, Tree and Sequences. Cambridge University Press, 1997.
J. Koza. Genetic programming-on the programming of computers by means of natural selection. Nature, 1993.
W. B. Langdon. Size fair and homologous tree genetic programming crossovers. In Proceedings of the Genetic and Evolutionary Computation Conference, volume 2, pages 1092–1097, Orlando, Florida, USA, 13–17 July 1999. Morgan Kaufmann.
V. I. Levenshtein. Binary codes capable of correcting deletions, insertions, and reversals. Soviet Physics-Doklady, 1966.
Peter Nordin, Wolfgang Banzhaf, and Frank D. Francone. Efficient evolution of machine code for CISC architectures using instruction blocks and homologous crossover. In Advances in Genetic Programming 3, chapter 12, pages 275–299. MIT Press, Cambridge, MA, USA, June 1999.
U. O’Reilly. Using a distance metric on genetic programs to understand genetic operators, 1997.
Tim Perkis. Stack-based genetic programming. In Proceedings of the 1994 IEEE World Congress on Computational Intelligence, volume 1, pages 148–153, Orlando, Florida, USA, 27–29 1994. IEEE Press.
Riccardo Poli and W. B. Langdon. Genetic programming with one-point crossover. In Soft Computing in Engineering Design and Manufacturing, pages 180–189. Springer-Verlag London, 23–27 June 1997.
William F. Punch, Douglas Zongker, and Erik D. Goodman. The royal tree problem, a benchmark for single and multiple population genetic programming. In Advances in Genetic Programming 2, chapter 15, pages 299–316. MIT Press, Cambridge, MA, USA, 1996.
R.E. Keller W. Banzhaf, P. Nordin and F.D. Francone. Genetic Programming-An Introduction. Morgan Kaufmann, 1998.
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2003 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Defoin Platel, M., Clergue, M., Collard, P. (2003). Maximum Homologous Crossover for Linear Genetic Programming. In: Ryan, C., Soule, T., Keijzer, M., Tsang, E., Poli, R., Costa, E. (eds) Genetic Programming. EuroGP 2003. Lecture Notes in Computer Science, vol 2610. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-36599-0_18
Download citation
DOI: https://doi.org/10.1007/3-540-36599-0_18
Published:
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-00971-9
Online ISBN: 978-3-540-36599-0
eBook Packages: Springer Book Archive