Evolving developmental neural networks to solve multiple problems

We describe a neural model in which two evolved neural programs undergo development and form neural networks. The programs decide whether neurons and their dendrites move, change, die or replicate. We show that the programs can build a neural structure from which multiple conventional ANNs can be extracted each of which can solve a different computational problem.