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C. FERREIRA In E. Lutton, J. A. Foster, J. Miller, C. Ryan, and A. G. B. Tettamanzi, eds., Proceedings of the 4th European Conference on Genetic Programming, Lecture Notes in Computer Science, Vol. 2278, pages 51-60, Springer-Verlag, Berlin, Germany, 2002.

Discovery of the Boolean Functions to the Best Density-Classification Rules Using Gene Expression Programming

Multigenic Chromosomes
 

GEP chromosomes are usually composed of more than one gene of equal length. For each problem or run, the number of genes, as well as the length of the head, are a priori chosen. Each gene codes for a sub-ET and the sub-ETs interact with one another forming a more complex multi-subunit ET.

Consider the following chromosome with length 45, composed of three genes:

012345678901234012345678901234012345678901234

Q/*b+Qababaabaa-abQ/*+bababbab**-*bb/babaaaab

(8)

It has three ORFs, and each ORF codes for a sub-ET. Position 0 marks the start of each gene. The end of each ORF, though, is only evident upon construction of the respective sub-ET. In this case, the first ORF ends at position 8; the second ORF ends at position 2; and the last ORF ends at position 10. Thus, GEP chromosomes are composed of one or more ORFs, each ORF coding for a structurally and functionally unique sub-ET. Depending on the problem at hand, the sub-ETs encoded by each gene may be selected individually according to their respective fitness (for example, in problems with multiple outputs), or they may form a more complex, multi-subunit ET where individual sub-ETs interact with one another by a particular kind of posttranslational interaction or linking. For instance, algebraic sub-ETs are usually linked by addition or multiplication whereas Boolean sub-ETs are usually linked by OR, AND, or IF.

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