Studying Parallel Evolutionary Algorithms: The cellular Programming Case

Capcarrere, Mathieu S., Tettamanzi, Andrea, Tomassini, Marco, Sipper, Moshe (1998) Studying Parallel Evolutionary Algorithms: The cellular Programming Case. In: Parallel Problem Solving from Nature V. 1498. pp. 573-582. Spriner-Verlag ISBN 0302-9743 (Print) 1611-3349 (Online). (doi:10.1007/BFb0056899) (KAR id:21608)

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Official URL: http://dx.doi.org/10.1007/BFb0056899
Additional URLs: http://citeseerx.ist.psu.edu/viewdoc/sum...

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)
DOI/Identification number:	10.1007/BFb0056899
Subjects:	Q Science > QA Mathematics (inc Computing science) > QA 76 Software, computer programming,
Institutional Unit:	Schools > School of Computing
Former Institutional Unit:	Divisions > Division of Computing, Engineering and Mathematical Sciences > School of Computing
Depositing User:	Mark Wheadon
Date Deposited:	25 Aug 2009 16:11 UTC
Last Modified:	20 May 2025 10:09 UTC
Resource URI:	https://kar.kent.ac.uk/id/eprint/21608 (The current URI for this page, for reference purposes)

University of Kent Author Information

Capcarrere, Mathieu S..

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