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170
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GECCO
2004
Springer
134views Optimization» more  GECCO 2004»
15 years 10 months ago
A Descriptive Encoding Language for Evolving Modular Neural Networks
Evolutionary algorithms are a promising approach for the automated design of artificial neural networks, but they require a compact and efficient genetic encoding scheme to repres...
Jae-Yoon Jung, James A. Reggia
129
Voted
GECCO
2004
Springer
15 years 10 months ago
On the Choice of the Population Size
Abstract. Evolutionary Algorithms (EAs) are population-based randomized optimizers often solving problems quite successfully. Here, the focus is on the possible effects of changin...
Tobias Storch
149
Voted
ICARIS
2004
Springer
15 years 10 months ago
A Fractal Immune Network
Proteins are the driving force in development (embryogenesis) and the immune system. Here we describe how a model of proteins designed for evolutionary development in computers can...
Peter J. Bentley, Jon Timmis
126
Voted
GECCO
2003
Springer
15 years 10 months ago
Theoretical Analysis of Simple Evolution Strategies in Quickly Changing Environments
Evolutionary algorithms applied to dynamic optimization problems has become a promising research area. So far, all papers in the area have assumed that the environment changes only...
Jürgen Branke, Wei Wang
GECCO
2003
Springer
15 years 10 months ago
Understanding EA Dynamics via Population Fitness Distributions
It is clear from the study of complex non-linear systems in general, and evolutionary algorithms (EAs) in particular, that there is no single analysis tool or technique capable of ...
Elena Popovici, Kenneth A. De Jong