Learning rules using genetic algorithms application to a knowledge base in an expert system generator

Cognitives sciences, artificial intelligence

Nowadays, progress in machine learning is phenomenal, thanks to the computing power of current computers. The application of this field is very large, ranging from mobile phone to industrial process control. In this article we used genetic algorithm for learning rules in order to incorporate into the knowledge base of an expert system. Our method is a supervised machine learning that uses VL2 language proposed by [1] and [2]. In order to reduce the length of chromosome, we transformed the bit string into integer according to [3] method which is detailed below. an expert system is software composed of a rule base, a fact base, an inference engine and a user interface. in order to automatically learn rules based on collected data we will incorporate a learning module into our expert system.

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