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.
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)|
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