Abstract
There have been many approaches to modularity in the field of evolutionary computation, each tailored to function with a particular representation. This research examines one approach to modularity and grammar modification with a grammar-based approach to genetic programming, grammatical evolution (GE). Here, GE’s grammar was modified over the course of an evolutionary run with modules in order to facilitate their appearance in the population. This is the first step in what will be a series of analysis on methods of modifying GE’s grammar to enhance evolutionary performance. The results show that identifying modules and using them to modify GE’s grammar can have a negative effect on search performance when done improperly. But, if undertaken thoughtfully, there are possible benefits to dynamically enhancing the grammar with modules identified during evolution.
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
Angeline, P.J., Pollack, J.: Evolutionary module acquisition. In: Fogel, D., Atmar, W. (eds.) Proceedings of the Second Annual Conference on Evolutionary Programming, La Jolla, CA, USA, February 25-26, pp. 154–163 (1993)
Angeline, P.J., Pollack, J.B.: The evolutionary induction of subroutines. In: Proceedings of the Fourteenth Annual Conference of the Cognitive Science Society, pp. 236–241. Lawrence Erlbaum, Bloomington (1992)
Garibay, O., Garibay, I., Wu, A.: The modular genetic algorithm: Exploiting regularities in the problem space. In: Yazıcı, A., Şener, C. (eds.) ISCIS 2003. LNCS, vol. 2869, pp. 584–591. Springer, Heidelberg (2003)
Harper, R., Blair, A.: Dynamically defined functions in grammatical evolution. In: Proceedings of the 2006 IEEE Congress on Evolutionary Computation, July 6-21, pp. 9188–9195. IEEE Press, Vancouver (2006)
Hemberg, E.: An Exploration of Grammars in Grammatical Evolution. Ph.D. thesis, University College Dublin (2010)
Hemberg, E., Gilligan, C., O’Neill, M., Brabazon, A.: A grammatical genetic programming approach to modularity in genetic algorithms. In: Ebner, M., O’Neill, M., Ekárt, A., Vanneschi, L., Esparcia-Alcázar, A.I. (eds.) EuroGP 2007. LNCS, vol. 4445, pp. 1–11. Springer, Heidelberg (2007)
Hemberg, E., O’Neill, M., Brabazon, A.: An investigation into automatically defined function representations in grammatical evolution. In: Matousek, R., Nolle, L. (eds.) 15th International Conference on Soft Computing, Mendel 2009, Brno, Czech Republic, June 24-26 (2009)
Holland, J.H.: Adaptation in natural and artificial systems. The University of Michigan Press, Ann Arbor (1975)
Keijzer, M., Ryan, C., Cattolico, M.: Run transferable libraries — learning functional bias in problem domains. In: Deb, K., et al. (eds.) GECCO 2004. LNCS, vol. 3103, pp. 531–542. Springer, Heidelberg (2004)
Koza, J.R.: Genetic Programming: on the Programming of Computers by Means of Natural Selection. MIT Press, Cambridge (1992)
Koza, J.R.: Architecture-altering operations for evolving the architecture of a multi-part program in genetic programming. Tech. rep., Stanford, CA, USA (1994)
Koza, J.R.: Genetic Programming II: Automatic Discovery of Reusable Programs. MIT Press, Cambridge (1994)
Majeed, H., Ryan, C.: Context-aware mutation: a modular, context aware mutation operator for genetic programming. In: GECCO 2007: Proceedings of the 9th Annual Conference on Genetic and Evolutionary Computation, pp. 1651–1658. ACM, New York (2007)
O’Neill, M., Ryan, C.: Grammatical Evolution: Evolutionary Automatic Programming in an Arbitrary Language. Kluwer Academic Publishers, Dordrecht (2003)
O’Neill, M., Vanneschi, L., Gustafson, S., Banzhaf, W.: Open issues in genetic programming. Genetic Programming and Evolvable Machines 11, 339–363 (2010)
Ryan, C., Keijzer, M., Cattolico, M.: Favourable biasing of function sets using run transferable libraries. In: Genetic Programming Theory and Practice II, pp. 103–120 (2005)
Simon, H.A.: The sciences of the artificial, 3rd edn. MIT Press, Cambridge (1996)
Walker, J., Miller, J.: The automatic acquisition, evolution and reuse of modules in cartesian genetic programming. IEEE Transactions on Evolutionary Computation 12(4), 397–417 (2008)
Whigham, P.: Inductive bias and genetic programming. In: First International Conference on Genetic Algorithms in Engineering Systems: Innovations and Applications, GALESIA (Conf. Publ. No. 414), September 1995, pp. 461–466 (1995)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2011 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Swafford, J.M., O’Neill, M., Nicolau, M., Brabazon, A. (2011). Exploring Grammatical Modification with Modules in Grammatical Evolution. In: Silva, S., Foster, J.A., Nicolau, M., Machado, P., Giacobini, M. (eds) Genetic Programming. EuroGP 2011. Lecture Notes in Computer Science, vol 6621. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-20407-4_27
Download citation
DOI: https://doi.org/10.1007/978-3-642-20407-4_27
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-20406-7
Online ISBN: 978-3-642-20407-4
eBook Packages: Computer ScienceComputer Science (R0)