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Abstract: Evolutionary learning has been developing rapidly in the last decade. It is a powerful and general learning approach which has been used successfully in both symbolic systems, e.g., rule-based systems, and subsymbolic systems, e.g., artificial neural networks. However, most evolutionary learning systems have paid little attention to the fact that they are population-based learning. The common practice is to select the best individual in the last generation as the final learned system. Such... (Update)
Context of citations to this paper: More
...in this section. There have been some very successful experiments which show that EA s can be used to evolve ANN ensembles [192] 193] [302] [305] D. Others There are some other novel combinations between ANN s and EA s. For example, Zitar and Hassoun [306] used EA s to...
...individual. The importance of making use of the information in a population has recently been demonstrated by evolving both ANN s [49] [50] and rule based systems [50] 51] The use of a second validation set al.so helps to prevent ANN s from overfitting the combined training...
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7: A population-based learning algorithm which learns both architectures and weight.. - Liu, Yao - 1996
7: Evolutionary Computation: Toward a New Philosophy of Machine Intelligence (context) - Fogel - 1995
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BibTeX entry: (Update)
X. Yao, Y. Liu, and P. Darwen, "How to make best use of evolutionary learning," in Complex Systems: From Local Interactions to Global Phenomena (R. Stocker, H. Jelinek, and B. Durnota, eds.), (Amsterdam), pp. 229--242, IOS Press, 1996. http://citeseer.ist.psu.edu/yao96how.html More
@misc{ yao96how,
author = "X. Yao and Y. Liu and P. Darwen",
title = "How to make best use of evolutionary learning",
text = "X. Yao, Y. Liu, and P. Darwen, How to make best use of evolutionary learning,
in Complex Systems: From Local Interactions to Global Phenomena (R. Stocker,
H. Jelinek, and B. Durnota, eds.), (Amsterdam), pp. 229--242, IOS Press,
1996.",
year = "1996",
url = "citeseer.ist.psu.edu/yao96how.html" }
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22 A population-based learning algorithm which learns both arch.. - Liu, Yao - 1996
19 person iterated prisoner's dilemma games (context) - Yao, Darwen et al. - 1995
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14 Evolutionary artificial neural networks that learn and gener.. - Yao, Liu - 1996
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The graph only includes citing articles where the year of publication is known.
Documents on the same site (http://www.cs.brandeis.edu/~darwen/publications.html): More
Viability of Populations in a Landscape - Darwen, Green (1996) (Correct)
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On Evolving Robust Strategies for Iterated Prisoner's Dilemma - And (1995) (Correct)
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