Studying Parallel Evolutionary Algorithms: The cellular Programming Case

Capcarrere, M. and Tettamanzi, A. and Tomassini, M. and Sipper, M. (1998) Studying Parallel Evolutionary Algorithms: The cellular Programming Case. In: Parallel Problem Solving from Nature V. (Full text available)

PDF
Download (245kB)
[img]
Preview
Official URL
http://dx.doi.org/10.1007/BFb0056899

Abstract

Parallel evolutionary algorithms, studied to some extent over the past few years, have proven empirically worthwhile—though there seems to be lacking a better understanding of their workings. In this paper we concentrate on cellular (fine-grained) models, presenting a number of statistical measures, both at the genotypic and phenotypic levels. We demonstrate the application and utility of these measures on a specific example, that of the cellular programming evolutionary algorithm, when used to evolve solutions to a hard problem in the cellular-automata domain, known as synchronization.

Item Type: Conference or workshop item (UNSPECIFIED)
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: 25 Aug 2009 16:11
Last Modified: 28 May 2012 14:56
Resource URI: http://kar.kent.ac.uk/id/eprint/21608 (The current URI for this page, for reference purposes)
  • Depositors only (login required):

Downloads

Downloads per month over past year