| Abstract: | Networks composed of layers of adaptive units provide a rigorous explanation for associative learning phenomena that otherwise have been relatively intractable, particularly learning to learn, spontaneous configuration, and negative patterning (the exclusive-OR problem). Layered network models can also reconcile these phenomena with better-understood phenomena, for example, stimulus summation, blocking, and conditioned inhibition. This article presents simulations based on a network of three adaptive units, each of which operates according to an associative competition rule, also known as the delta rule. (PsycINFO Database Record (c) 2010 APA, all rights reserved) |
