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» Selecting for evolvable representations
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CEC
2009
IEEE
14 years 2 months ago
Evolving modular neural-networks through exaptation
— Despite their success as optimization methods, evolutionary algorithms face many difficulties to design artifacts with complex structures. According to paleontologists, living...
Jean-Baptiste Mouret, Stéphane Doncieux
GECCO
2006
Springer
171views Optimization» more  GECCO 2006»
13 years 11 months ago
Evolving ensemble of classifiers in random subspace
Various methods for ensemble selection and classifier combination have been designed to optimize the results of ensembles of classifiers. Genetic algorithm (GA) which uses the div...
Albert Hung-Ren Ko, Robert Sabourin, Alceu de Souz...
RAID
2009
Springer
14 years 2 months ago
Using Formal Grammar and Genetic Operators to Evolve Malware
In this paper, we leverage the concepts of formal grammar and genetic operators to evolve malware. As a case study, we take COM infectors and design their formal grammar with produ...
Sadia Noreen, Shafaq Murtaza, M. Zubair Shafiq, Mu...
GECCO
2009
Springer
14 years 2 months ago
The relationship between evolvability and bloat
Bloat is a common problem with Evolutionary Algorithms (EAs) that use variable length representation. By creating unnecessarily large individuals it results in longer EA runtimes ...
Jeffrey K. Bassett, Mark Coletti, Kenneth A. De Jo...
GECCO
2000
Springer
127views Optimization» more  GECCO 2000»
13 years 11 months ago
Evolving Molecules for Drug Design Using Genetic Algorithms via Molecular Trees
We present a new representation for a genetic algorithm to evolve molecular structures representing possible drugs that bind to a given protein target receptor. Our representation...
Gerard Kian-Meng Goh, James A. Foster