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After the new generation is bred, genetic programming looks at the new population to see if any of the individuals solve the problem. In genetic programming terms, this usually means evaluating the "fitness" of each individual (a numeric score that measures the ability of the individual). If any individual is "fit enough", the evolutionary search stops.


This is a generics-based implementation of a genetic programming population. For the RSGeneticProgramming|TRSGeneticProgramming class, the generics class is instantiated as floating point values. However, you can define your own genetic programming component using whatever type you want.


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