  There are a number of ways to procedurally generate interesting
three-dimensional shapes, and a method where a cellular neural network is
combined with a mesh growth algorithm is presented here. The aim is to create a
shape from a genetic code in such a way that a crude search can find
interesting shapes. Identical neural networks are placed at each vertex of a
mesh which can communicate with neural networks on neighboring vertices. The
output of the neural networks determine how the mesh grows, allowing
interesting shapes to be produced emergently, mimicking some of the complexity
of biological organism development. Since the neural networks' parameters can
be freely mutated, the approach is amenable for use in a genetic algorithm.
