Evolving the morphology of a neural network for controlling a foveating retina: and its test on a real robot

Abstract

The standard approach in evolutionary robotics is to evolve neural networks for control by encoding the parameters of the network in the genome. By contrast, we have evolved a neural controller based on biological principles from molecular and developmental biology. The key principles employed in our algorithms model the specific ligand-receptor interactions and gene regulation.