I've read about NEAT/Evolutionary Artificial Neural Networks/Genetic Algorithms.
I understand the concept of choosing the fittest neural networks and breeding them to produce another one, but how exactly does this work?
Do you simply choose at random, weights from the parents, for the child network? Do you cross over the bias weights too?
How would this produce a network as fit as its parents, would it not just produce a new random network, because the weights have lost their correlation?
After trying this weight-swapping, I got very bad results.
What are the in-depth steps to evolving a feed-forward neural network?
Something like this