Natural Coding: A More Efficient Representation for Evolutionary Learning-Reference-Cited by-同舟云学术

Natural Coding: A More Efficient Representation for Evolutionary Learning

Published:2003 Issue: Volume: Page:979-990
ISSN:0302-9743
Container-title:Genetic and Evolutionary Computation — GECCO 2003
language:
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Author:

Giráldez Raúl,Aguilar-Ruiz Jesús S.,Riquelme José C.

Publisher

Springer Berlin Heidelberg

Link

http://link.springer.com/content/pdf/10.1007/3-540-45105-6_109

Reference23 articles.

1. Jesus S. Aguilar-Ruiz and J.C. Riquelme. Improving the Evolutionary Coding for Machine Learning Tasks. European Conference on Artificial Intelligence, ECAI’02, pp. 173–177, IOS Press, Lyon, France, 2002.

2. Jesus S. Aguilar-Ruiz, J.C. Riquelme and M. Toro. Evolutionary Learning of Hierarchical Decision Rules. IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics, ISSN: 1083-4419, vol. 33, no. 2, pp. 324–331, 2003.

3. J. Antonisse. A new interpretation of schema notation that overturns the binary encoding constraint. In: Third International Conference on Genetic Algorithms, pp. 86–97, 1989.

4. S. Bhattacharyya and G. Koehler. An analysis of non-binary genetic algorithms with cardinality 2v. Complex Systems 8, pp. 227–256, 1994.

5. C. Blake and E. K. Merz. UCI repository of machine learning databases, 1998.

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