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 |
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) |
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DOI/Identification number: | 10.1007/BFb0056899 |
Subjects: | Q Science > QA Mathematics (inc Computing science) > QA 76 Software, computer programming, |
Divisions: | 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: | 16 Nov 2021 09:59 UTC |
Resource URI: | https://kar.kent.ac.uk/id/eprint/21608 (The current URI for this page, for reference purposes) |
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