I didn't find any literature on this matter; I want to build an RNN that uses both Genetic algorithms and back propagation to evolve a network. So my idea is to use GA and BP for training, though in a newer way:
For optimization of the weights we will use BP.
For creating new layers, new edges and nodes in the graph using mutation and fitness, namely GA.
What do you think about this approach, why people haven not done it before?