Neurocybernetic machines: Adaptivity by homeostatic neurons

Following the Artificial Life approach to Evolutionary Robotics the goal of Neurocybernetic Machines is to test hypotheses on the possible realization of artificial cognitive systems. In this context self-organization in the form of synaptic plasticity of neural networks serving as control systems for autonomous mobile robots is an interesting subject to study. We introduce an approach to adaptivity and plasticity of controllers based on homeostatic neurons and discuss its relation to structure evolution of neural controllers.