Adaptive State Representation and Estimation Using Recurrent Connectionist Networks
Introduction The purpose of this chapter is to provide an introductory overview of some of the current research efforts directed toward adapting the weights in connectionist networks having feedback connections. While much of the recent emphasis in the field has been on multilayer networks having no such feedback connections, it is likely that the use of recurrently connected networks will be of particular importance for applications to the control of dynamical systems. Following the approach taken in the previous chapter by Andy Barto, this chapter will emphasize the relationship of connectionist research in this area to strategies used in more conventional engineering circles for modelling and controlling dynamical systems, while at the same time noting what there is in the connectionist approach that is novel. In particular, I will argue that while much of the connectionist approach to adapting the weights in recurrent networks having interesting dynamics rests on the same