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GECCO
2004
Springer
134views Optimization» more  GECCO 2004»
16 years 6 days 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
GECCO
2004
Springer
16 years 6 days 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
ICARIS
2004
Springer
16 years 6 days 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
GECCO
2003
Springer
16 years 1 days 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
16 years 1 days 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