There has been a recent interest in combining genetic algorithms and neural networks into a general neuroevolution framework. The basic idea, is that your genetic algorithm is evolving the parameters of many neural-network which are then used to solve your task at hand. A sort of genetic programming but instead of evolving a snippet of code to do some task, you are evolving a neural network.
When should I use this combined approach instead of using neural-networks or genetic algorithms by themselves? For what types of problems has the combined approach produced better results that the individual approaches? For what types of problems is the combined approach the 'best' approach?