Paper Info
Title
Neural Networks And Adaptive Expert Systems In The Csa Approach
Abstract
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.
Year
DOI
Venue
1993
10.1002/int.4550080407
INTERNATIONAL JOURNAL OF INTELLIGENT SYSTEMS
Keywords
Field
DocType
expert system,neural network
Computer science,Parallel search,Expert system,Artificial intelligence,Artificial neural network,Rule of inference,Genetic algorithm,Machine learning,Symbolic method,Computation,Legal expert system
Journal
Volume
Issue
ISSN
8
4
0884-8173
Citations 
PageRank 
References 
7
1.18
6
Authors
1
Name
Order
Citations
PageRank
Eugeniusz Eberbach1388.70