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Gene Expression Programming: Mathematical Modeling by an Artificial Intelligence


Karva language: The language of GEP 

We have seen that each gene codes for a particular subET, and that each subET corresponds to a specific Kexpression or open reading frame. Due to the simplicity and elegance of this correspondence, Kexpressions are, per se, extremely compact, intelligible computer programs. We have seen how multisubunit ETs can be easily converted into linear Kexpressions, and this can be easily done for any algebraic, Boolean, or nonconventional expression. Indeed, the language of GEP – Karva language – is a versatile representation that can be used to evolve relatively complex programs as simple, extremely compact, symbolic strings. In fact, there is already commercially available software such as
Automatic Problem Solver by Gepsoft which automatically converts Kexpressions and GEP chromosomes into conventional C++ or Visual Basic functions.
Another advantage of Karva notation is that it can be used to evolve complex programs using any programming language. Indeed, the original GEP implementation was written in C++, but it can be done in virtually any programming language. As a comparison, it is worth mentioning that early GP implementations relied greatly on LISP because it is simple to do the subtree swapping that occurs during reproduction with this language. In the
next chapter, the implementation details of the gene expression algorithm will be fully analyzed, starting with creating an initial population and finishing with selection and reproduction.


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