Analysing recurrent dynamical networks evolved for robot control

This paper has outlined a framework in which we are using artificial evolution to develop arbitrarily recurrent continuous dynamical neural networks to generate robust behaviour in autonomous mobile robots. It is shown how evolved networks, although at first sight rather complex, can be understood with a mixture of qualitative and quantitative analysis