Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Genetic cellular neural networks for generating three-dimensional
  geometry   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.

17
The categories of this paper are: q-fin
30
The categories of this paper are: q-alg
16
The categories of this paper are: stat
22
The categories of this paper are: chao-dyn
35
The categories of this paper are: mtrl-th
29
The categories of this paper are: funct-an
11
The categories of this paper are: hep-lat
25
The categories of this paper are: patt-sol
21
The categories of this paper are: adap-org
13
The categories of this paper are: quant-ph
32
The categories of this paper are: atom-ph
7
The categories of this paper are: hep-th
34
The categories of this paper are: chem-ph
23
The categories of this paper are: solv-int
24
The categories of this paper are: dg-ga
8
The categories of this paper are: hep-ex