Publication Type

Journal Article

Version

publishedVersion

Publication Date

6-1991

Abstract

A neural network expert system called adaptive connectionist expert system (ACES) which will learn adaptively from past experience is described. ACES is based on the neural logic network, which is capable of doing both pattern processing and logical inferencing. The authors discuss two strategies, pattern matching ACES and rule inferencing ACES. The pattern matching ACES makes use of past examples to construct its neural logic network and fine-tunes itself adaptively during its use by further examples supplied. The rule inferencing ACES conceptualizes new rules based on the frequencies of use on the rule-based neural logic network. A new rule could be considered as a pattern matching example and be incorporated into pattern matching ACES.

Keywords

Hybrid intelligent systems, Adaptive systems, Pattern matching, Diagnostic expert systems, Neural networks, Logic programming, Expert systems, Knowledge acquisition, Medical expert systems, Frequency

Discipline

Databases and Information Systems

Research Areas

Data Science and Engineering

Publication

IEEE Transactions on Knowledge and Data Engineering

Volume

3

Issue

2

First Page

200

Last Page

207

ISSN

1041-4347

Identifier

10.1109/69.88000

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Copyright Owner and License

Publisher

Additional URL

https://doi.org/10.1109/69.88000

Share

COinS