ABSTRACT
GAGS is a C++ class library designed to make programming a Genetic Algorithm (GA) and flexible enough to add new objects, which are treated in the same way as native ones. Chromosomes are the basic building blocks of a genetic algorithm and are used to represent a problem solution. Some operators are variable-length operators: they alter the length of the chromosome. Chromosome length is always computed in every method that needs it, which means that GAGS is prepared for variable length chromosomes. Genetic operators are used in genetic algorithms to generate diversity and to combine existing solutions into others, decreasing diversity. In GAGS, operators constitute a class, that is, they are not methods of the usual chromosome class. Designing a good neural network (NN) for patter recognition has always been a problem in the neural net community. Most of the times, NN parameters and policies are chosen resorting to past experience.
