Fast Adaptation with Random Neural Networks


By Erol Gelenbe, Imperial College, London


We will describe how the recurrent structure of Random Neural Networks, and their approximation and convergence properties, can be exploited to adaptively control large systems such as packet networks on the one hand, and intricate texture patterns at the other end. The talk will summarize the underlying theory, and present working systems based on these principles.