Designing Cellular Automata Using a Parallel Evolutionary Algorithm

Sipper, Moshe and Tomassini, Marco and Capcarrere, Mathieu S. (1997) Designing Cellular Automata Using a Parallel Evolutionary Algorithm. Nuclear Instruments and Methods in Physics Research Section A: Accelerators, Spectrometers, Detectors and Associated Equipment, 389 (1-2). pp. 278-283. ISSN 0168-9002 . (The full text of this publication is not currently available from this repository. You may be able to access a copy if URLs are provided)

The full text of this publication is not available from this repository. (Contact us about this Publication)
Official URL


We have previously shown that non-uniform Cellular Automata (CA) can be evolved to perform computational tasks, using the cellular programming evolutionary algorithm. In this paper we focus on two novel issues, namely the evolution of asynchronous CAs, and the fault tolerance of our evolved systems. We find that asynchrony presents a more difficult case for evolution though good CAs can still be attained. We show that our evolved systems exhibit graceful degradation in performance, able to tolerate a certain level of faults. Our motivation for this study stems in part by our desire to attain realistic systems that are more amenable to implementation as 'evolving ware', evolware.

Item Type: Article
Additional information: This paper was also in ASIHENP'96 proceedings, World Scientific Pulbishing Company.
Uncontrolled keywords: Non-uniform cellular automata; Asynchronous cellular automata; Cellular programming; Evolutionary computation; Fault tolerance; Evolware
Subjects: Q Science > QA Mathematics (inc Computing science) > QA 76 Software, computer programming,
Divisions: Faculties > Science Technology and Medical Studies > School of Computing > Applied and Interdisciplinary Informatics Group
Depositing User: Mark Wheadon
Date Deposited: 24 Jul 2009 21:58
Last Modified: 01 May 2014 08:55
Resource URI: (The current URI for this page, for reference purposes)
  • Depositors only (login required):


Downloads per month over past year