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GECCO
2007
Springer
276views Optimization» more  GECCO 2007»
15 years 4 months ago
Automatic mutation test input data generation via ant colony
Fault-based testing is often advocated to overcome limitations of other testing approaches; however it is also recognized as being expensive. On the other hand, evolutionary algor...
Kamel Ayari, Salah Bouktif, Giuliano Antoniol
GECCO
2007
Springer
160views Optimization» more  GECCO 2007»
15 years 4 months ago
Self-modifying cartesian genetic programming
In nature, systems with enormous numbers of components (i.e. cells) are evolved from a relatively small genotype. It has not yet been demonstrated that artificial evolution is su...
Simon Harding, Julian Francis Miller, Wolfgang Ban...
GECCO
2007
Springer
119views Optimization» more  GECCO 2007»
15 years 4 months ago
Optimising the flow of experiments to a robot scientist with multi-objective evolutionary algorithms
A Robot Scientist is a physically implemented system that applies artificial intelligence to autonomously discover new knowledge through cycles of scientific experimentation. Ad...
Emma Byrne
GECCO
2007
Springer
168views Optimization» more  GECCO 2007»
15 years 4 months ago
Empirical analysis of generalization and learning in XCS with gradient descent
We analyze generalization and learning in XCS with gradient descent. At first, we show that the addition of gradient in XCS may slow down learning because it indirectly decreases...
Pier Luca Lanzi, Martin V. Butz, David E. Goldberg
GECCO
2007
Springer
178views Optimization» more  GECCO 2007»
15 years 4 months ago
Discussion of parallel model of multi-objective genetic algorithms on heterogeneous computational resources
— In this paper, a parallel model of multi-objective genetic algorithm supposing a grid environment is discussed. In this proposed parallel model, we extended master-slave model ...
Tomoyuki Hiroyasu, Kengo Yoshii, Mitsunori Miki