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An improved representation for evolving programs

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journal contribution
posted on 04.03.2009, 13:29 by Mark S. Withall, Christopher Hinde, Roger StoneRoger Stone
A representation has been developed that addresses some of the issues with other Genetic Program representations while maintaining their advantages. This combines the easy reproduction of the linear representation with the inherita- ble characteristics of the tree representation by using fixed-length blocks of genes representing single program statements. This means that each block of genes will always map to the same statement in the parent and child unless it is mutated, irrespective of changes to the surrounding blocks. This method is compared to the variable length gene blocks used by other representations with a clear improvement in the similarity between parent and child. In addition, a set of list evaluation and manipulation functions was evolved as an application of the new Genetic Program components. These functions have the common feature that they all need to be 100% correct to be useful. Traditional Genetic Programming problems have mainly been optimization or approximation problems. The list results are good but do highlight the problem of scalability in that more complex functions lead to a dramatic increase in the required evolution time.

History

School

  • Science

Department

  • Computer Science

Citation

WITHALL, M.S., HINDE, C.J. and STONE, R.G., 2009. An improved representation for evolving programs. Genetic Programming and Evolvable Machines, 10 (1), pp. 37-70

Publisher

© Springer Science+Business Media

Version

AM (Accepted Manuscript)

Publication date

2009

Notes

This article was published in the journal, Genetic Programming and Evolvable Machines [© Springer Science+Business Media]. The original publication is available at www.springerlink.com http://dx.doi.org/10.1007/s10710-008-9069-7

ISSN

1389-2576

Language

en