Publication detail

Learning methods in expert systems

VALENTA, J.

Original Title

Learning methods in expert systems

Type

lecture

Language

English

Original Abstract

This presentation describes learning methods used in expert systems. The motivation for learning knowledge-bases in expert systems is there presented, as well as the basic of an expert system. Presentation introduced a method to eliminate knowledge engineer from the process of expert system's knowledge base creation. The methods developed for this task are mainly based on fusion of neural networks and rules. Two basic algorithms are shortly presented here and their advantages and shortcomings are noticed. These methods are compared with two developed methods for the direct learning of rule-based systems. One of the methods consists on a modification of back-propagation algorithm to learn the rule base directly and the other is based on evolutionary computation with special uncertainty processing. The structure, properties and method of learning are presented, as well as the process of using the algorithm and its main advantages. Finally is introduced an implementation of the learning algorithms in a real expert system.

Authors

VALENTA, J.

Released

5. 12. 2007

Location

Coimbra, Portugalsko

BibTex

@misc{BUT64768,
  author="Jan {Valenta}",
  title="Learning methods in expert systems",
  year="2007",
  address="Coimbra, Portugalsko",
  note="lecture"
}