HyperNEAT
Hypercube-based NEAT, or HyperNEAT, is a generative encoding that evolves artificial neural networks with the principles of the widely used NeuroEvolution of Augmented Topologies algorithm. It is a novel technique for evolving large-scale neural networks using the geometric regularities of the task domain. It uses Compositional Pattern Producing Networks , which are used to generate the images for and shapes for . HyperNEAT has recently been extended to also evolve plastic ANNs and to evolve the location of every neuron in the network.
