Would be interesting to use this as a training algorithm -- have multiple self-replicating networks that mate and copy portions of their weights in random patterns... eerie.

We already have the mating part with NeatAI. Link: http://nn.cs.utexas.edu/downloads/papers/stanley.ec02.pdf

Essentially it's a neural network which is represented by a series of genes. Genetically, new genes come in by having new links form between neurons, disabled, or split (with an in between neuron). This, as you can see, allows for a wide range of network representations. Because these variations are tagged with id's sequentially, we can mate two neural networks by combining their genes in order. They never conflict, and will produce something similar to both parents.

Create fitness vectors based on their performance over to different problem types to create competition in the environment.

haha. alas, paper appears to cover asexual reproduction of neural networks only

That'll be fixed when the Uni PR department issues the press release.