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Some Genetic Algorithm frameworks, such as http://www.aforgenet.com/ requires many parameters, such as mutation rate, population size, etc
There is universal best numbers for such parameters? I believe that it depends on the problem (fitness function delay, mutation delay, recombination delay, evolution rate, etc). My first thought was to use a GA to configure another GA.
Any better ideas?
The one time I programmed a genetic algorithm I included those values in the values to mutate, basically like you said using a GA to configure itself. It worked surprisingly well, especially since I’ve found it to be beneficial for those values to change over the course of it’s computation.