Dybowski, R.; Collins, T. D. and Weller, P. R.
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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.
|Item Type:||Conference Item|
|Copyright Holders:||1996 MIT Press|
|Project Funding Details:||
|Extra Information:||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/Department:||Knowledge Media Institute|
|Interdisciplinary Research Centre:||Centre for Research in Computing (CRC)|
|Depositing User:||Kay Dave|
|Date Deposited:||17 May 2011 12:52|
|Last Modified:||24 Mar 2016 21:32|
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