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C. FERREIRA In A. Abraham, J. Ruiz-del-Solar, and M. Köppen (eds), Soft Computing Systems: Design, Management and Applications, pp. 153-162, IOS Press, Netherlands, 2002.

Analyzing the Founder Effect in Simulated Evolutionary Processes Using Gene Expression Programming

Gene Expression Programming
The phenotype of GEP individuals consists of the same kind of ramified structures used in genetic programming. However, these complex entities are encoded in simpler, linear structures of fixed length – the chromosomes. Thus, there are two main players in GEP: the chromosomes and the ramified structures or expression trees (ETs), the latter being the expression of the genetic information encoded in the former. As in nature, the process of information decoding is called translation. And this translation implies obviously a kind of code and a set of rules. The genetic code is very simple: a one-to-one relationship between the symbols of the chromosome and the functions or terminals they represent. The rules are also very simple: they determine the spatial organization of the functions and terminals in the ETs and the type of interaction between sub-ETs in multigenic systems.

In GEP there are therefore two languages: the language of the genes and the language of ETs. However, thanks to the simple rules that determine the structure of ETs and their interactions, it is possible to infer immediately the phenotype given the sequence of a gene, and vice versa. This bilingual and unequivocal system is called Karva language. The details of this new language are given in [4].

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