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Dybowski, R.; Collins, T. D. and Weller, P. R.
(1996).
URL: http://mitpress.mit.edu/catalog/item/default.asp?t...
Abstract
Understanding the evolution of a complex genetic algorithm is a non-trivial problem, however, genetic-algorithm visualization is in its infancy. This paper reviews some of the current approaches and presents a new visualization approach based on Sammon mapping. Sammon mapping is a nonlinear mapping of a set of vectors in p-dimensional space to a set in r-dimensional space, where r < p. The mapping attempts to preserve in r-space the Euclidean inter-vector distances present in p-space. We demonstrate that a Sammon mapping to 2-space of binary chromosomes present in a higher-dimensional allele space during the execution of a genetic algorithm can indicate the presence of multiple solutions. Shortfalls of this approach are discussed along with possible solutions.
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- Item ORO ID
- 28582
- Item Type
- Conference or Workshop Item
- Project Funding Details
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Funded Project Name Project ID Funding Body Not Set Not Set Special Trustees for St Thomas' Hospital (London) Not Set Not Set EPSRC (Engineering and Physical Sciences Research Council) - Extra Information
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Workshop Proceedings ISBN: 9781874152040
Conference Proceedings ISBN: 978-0-262-06190-2
The Proceedings of the Fifth Annual Conference on Evolutionary Programming (EP96), MIT Press.
San Diego, CA. Edited by L.J. Fogel, P.J. Angeline, and T. Baeck. pages 377 - 38 - Academic Unit or School
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Faculty of Science, Technology, Engineering and Mathematics (STEM) > Knowledge Media Institute (KMi)
Faculty of Science, Technology, Engineering and Mathematics (STEM) - Research Group
- Centre for Research in Computing (CRC)
- Copyright Holders
- © 1996 MIT Press
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- Depositing User
- Kay Dave
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CORE (COnnecting REpositories)