IRMA-International.org: Creator of Knowledge
Information Resources Management Association
Advancing the Concepts & Practices of Information Resources Management in Modern Organizations

Gene Expression Programming and the Evolution of Computer Programs

Gene Expression Programming and the Evolution of Computer Programs
View Sample PDF
Author(s): Cândida Ferreira (Gepsoft, UK)
Copyright: 2005
Pages: 22
Source title: Recent Developments in Biologically Inspired Computing
Source Author(s)/Editor(s): Leandro Nunes de Castro (Mackenzie University, Brazil) and Fernando J. Von Zuben (State University of Campinas, Brazil)
DOI: 10.4018/978-1-59140-312-8.ch005

Purchase

View Gene Expression Programming and the Evolution of Computer Programs on the publisher's website for pricing and purchasing information.

Abstract

In this chapter an artificial problem solver inspired in natural genotype/phenotype systems — gene expression programming — is presented. As an introduction, the fundamental differences between gene expression programming and its predecessors, genetic algorithms and genetic programming, are briefly summarized so that the evolutionary advantages of gene expression programming are better understood. The work proceeds with a detailed description of the architecture of the main players of this new algorithm (chromosomes and expression trees), focusing mainly on the interactions between them and how the simple yet revolutionary structure of the chromosomes allows the efficient, unconstrained exploration of the search space. And finally, the chapter closes with an advanced application in which gene expression programming is used to evolve computer programs for diagnosing breast cancer.

Related Content

Mohamed Arezki Mellal. © 2022. 9 pages.
Tahir Cetin Akinci, Ramazan Caglar, Gokhan Erdemir, Aydin Tarik Zengin, Serhat Seker. © 2022. 11 pages.
Sunanda Hazra, Provas Kumar Roy. © 2022. 16 pages.
Ragab A. El-Sehiemy, Almoataz Y. Abdelaziz. © 2022. 23 pages.
Khaled Dassa, Abdelmadjid Recioui. © 2022. 35 pages.
Anupama Kumari, Mukund Madhaw, C. B. Majumder, Amit Arora. © 2022. 21 pages.
Mandrita Mondal. © 2022. 20 pages.
Body Bottom