Studying Parallel Evolutionary Algorithms: The cellular Programming Case

Capcarrere, Mathieu S. and Tettamanzi, Andrea and Tomassini, Marco and Sipper, Moshe (1998) Studying Parallel Evolutionary Algorithms: The cellular Programming Case. In: Parallel Problem Solving from Nature V. (doi: (Full text available)

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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 > Sciences > School of Computing > Applied and Interdisciplinary Informatics Group
Depositing User: Mark Wheadon
Date Deposited: 25 Aug 2009 16:11 UTC
Last Modified: 12 Jun 2014 08:20 UTC
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