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GECCO
2007
Springer
151views Optimization» more  GECCO 2007»
16 years 1 months ago
Solving real-valued optimisation problems using cartesian genetic programming
Classical Evolutionary Programming (CEP) and Fast Evolutionary Programming (FEP) have been applied to realvalued function optimisation. Both of these techniques directly evolve th...
James Alfred Walker, Julian Francis Miller
GECCO
2007
Springer
437views Optimization» more  GECCO 2007»
16 years 1 months ago
A gestalt genetic algorithm: less details for better search
The basic idea to defend in this paper is that an adequate perception of the search space, sacrificing most of the precision, can paradoxically accelerate the discovery of the mo...
Christophe Philemotte, Hugues Bersini
GECCO
2007
Springer
183views Optimization» more  GECCO 2007»
16 years 1 months ago
Distribution replacement: how survival of the worst can out perform survival of the fittest
A new family of "Distribution Replacement” operators for use in steady state genetic algorithms is presented. Distribution replacement enforces the members of the populatio...
Howard Tripp, Phil Palmer
GECCO
2007
Springer
194views Optimization» more  GECCO 2007»
16 years 1 months ago
Hybrid coevolutionary algorithms vs. SVM algorithms
As a learning method support vector machine is regarded as one of the best classifiers with a strong mathematical foundation. On the other hand, evolutionary computational techniq...
Rui Li, Bir Bhanu, Krzysztof Krawiec
GECCO
2007
Springer
138views Optimization» more  GECCO 2007»
16 years 1 months ago
Unwitting distributed genetic programming via asynchronous JavaScript and XML
The success of a genetic programming system in solving a problem is often a function of the available computational resources. For many problems, the larger the population size an...
Jon Klein, Lee Spector
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