it's a pretty standard procedure to train NNs through GAs but usually not very efficient (e.g. compared to backtracking). in some cases you might lack an easy

it's a pretty standard procedure to train NNs through GAs but usually not very efficient (e.g. compared to backtracking). in some cases you might lack an easy way to calculate a fitness score out of the NN performance, which is needed to run the GA. i tried training a simple NN with a stupid hill climber some time ago but quickly hit a roadblock even with very few neurons because of local minima ... or maybe bugs. i guess for more complicated problems the pure GA training method might just not be "cost effective" (i.e. time/quality tradeoff).