Neural networks and adaptive expert systems in the CSA approach
Eugene Eberbach · International Journal of Intelligent Systems · 1993
According to many authors, neural networks and adaptive expert systems may provide the foundations of sixth-generation computers. Neural networks use lower hardware-like concepts and they are based on continuous and numeric type computation. On the other hand, adaptive expert systems use inference rules and perform high-level symbolic computations. the approaches may seem to be totally different, but they do exhibit similar properties: learning, flexibility, parallel search, generalization, and association. This article takes up the problem of the design of a common model for neural networks and adaptive expert systems. For this purpose the Calculus of Self-Modifiable Algorithms, a general tool for problem solving, is used. This joint approach to expert systems and neural networks emphasize their analogies, rather than their differences. © 1993 John Wiley & Sons, Inc.