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.
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| Official URL http://dx.doi.org/10.1007/BFb0056899 |
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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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| 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) |
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