Neurobiology suggests the design of modular architectures for neural control
J.L. Buessler, Jean-Philippe Urban · Advanced Robotics · 2002
The existence of modular structures in the biological world strongly suggests that the training of this kind of structure is actually feasible. It is a key indication for the development of neural network applications, especially in the field of robotics. Indeed, a single network can only efficiently treat problems with few independent variables; the combination of several networks is necessary to address more complex tasks. We investigate learning techniques and show that using a particular form of architecture can ease the training of a modular structure: a bi-directional structure that allows combining several neural networks. The approach is illustrated with Kohonen's self-organizing maps for a robotic visual servoing task.