Intelligent control with hierarchical stacked neural networks

Abstract

An intelligent control system based on an explicit model of cognitive development (Table 1) performs high-level functions. It comprises up to O hierarchically stacked neural networks, N, . . . , N+(O−1), where m denotes the stage/order tasks performed in the first neural network, N, and O denotes the highest stage/order tasks performed in the highest-level neural network. The type of processing actions performed in a network, N, corresponds to the complexity for stage/order m. Thus Nperforms tasks at the level corresponding to stage/order 1. Nprocesses information at the level corresponding to stage/order 5. Stacked neural networks begin and end at any stage/order, but information must be processed by each stage in ascending order sequence. Stages/orders cannot be skipped. Each neural network in a stack may use different architectures, interconnections, algorithms, and training methods, depending on the stage/order of the neural network and the type of intelligent control system implemented.