Overview of the model. A. Individuals and resources are placed on a grid (size 100×100). Individuals consist of a genome, from which a network is computed. They compete for reproduction into empty grid sites by processing resources. B. The resource is a bit string of length 64. Maximally the first 8 bits can be sensed by a network, which then produces a sequence of bits at its output. The output is matched to the original bit string, and the length of the correct sequence (matching the bit string from the leftmost bit) is the raw score of the individual, which in this example is 13. If the individual reproduces, the resource is rotated from right to left for 13 bits and placed back in the grid site. C. The effect of a few types of mutation on the genome (left) and the topology of the network (right). By default the parameter values for each type of mutation are: gene duplication 16·10-4, deletion 24·10-4, binding specificity 4·10-4, gene expression threshold 4·10-4, binding site duplication 4·10-4, deletion 10·10-4, innovation 1·10-4, binding specificity 4·10-4, weight 4·10-4. In order to balance the growth of the network, we apply a small penalty per gene and binding site of pen = 2.5·10-5.