---
title: "Learning Concept Classification Rules Using Genetic Algorithms"
authors:
  - "Kenneth A. De Jong"
  - "William M. Spears"
doi: ""
url: "https://ijcai.org/proceedings/1991/95"
pdf: "https://ijcai.org/proceedings/1991/0095.pdf"
venue: "Proceedings of the Twelfth International Joint Conference on Artificial Intelligence"
year: 1991
pages: "651-656"
track: "Learning Be Knowledge Acquisition"
keywords:
---

# Learning Concept Classification Rules Using Genetic Algorithms

Kenneth A. De Jong, William M. Spears

*Proceedings of the Twelfth International Joint Conference on Artificial Intelligence*, pages 651-656.

## Abstract

In this paper we explore the use of an adaptive search technique (genetic algorithms) to construct a system GABIL which continually learns and refines concept classification rules from its interaction with the environment. The performance of the system is measured on a set of concept learning problems and compared with the performance of two existing systems: IDSR and C4.5. Preliminary results support that, despite minimal system bias, GABIL is an effective concept learner and is quite competitive with ID5R and C4.5 as the target concept increases in complexity.