Genetic programming for expert systems

Sickel K, Hornegger J (2010)


Publication Type: Conference contribution, Conference Contribution

Publication year: 2010

Original Authors: Sickel K., Hornegger J.

Book Volume: null

Pages Range: -

Event location: Barcelona

Journal Issue: null

DOI: 10.1109/CEC.2010.5586200

Abstract

Genetic programming is the usage of the paradigm of survival of the fittest in scientific computing. It is applied to evolve solutions to problems where dependencies between multiple input factors are unknown. In this paper we propose and evaluate the application of a specifically adapted genetic programming framework to optimize the rule base of an expert system. The expert system controls a computer-aided-design software and targets the automation of a manufacturing process. The used steady state genetic programming framework introduces some variations on the selection and evolution operators normally used in genetic programming. In particular: size enforcing mutation, dynamic fitness calculation and size constraint ranking. The genetic programming system is evaluated with real data and led to an improved expert system performance of about 22 percent. © 2010 IEEE.

Authors with CRIS profile

How to cite

APA:

Sickel, K., & Hornegger, J. (2010). Genetic programming for expert systems. In Proceedings of the 2010 6th IEEE World Congress on Computational Intelligence, WCCI 2010 - 2010 IEEE Congress on Evolutionary Computation, CEC 2010 (pp. -). Barcelona.

MLA:

Sickel, Konrad, and Joachim Hornegger. "Genetic programming for expert systems." Proceedings of the 2010 6th IEEE World Congress on Computational Intelligence, WCCI 2010 - 2010 IEEE Congress on Evolutionary Computation, CEC 2010, Barcelona 2010. -.

BibTeX: Download