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GECCO
2006
Springer
157views Optimization» more  GECCO 2006»
13 years 12 months ago
gLINC: identifying composability using group perturbation
We present two novel perturbation-based linkage learning algorithms that extend LINC [5]; a version of LINC optimised for decomposition tasks (oLINC) and a hierarchical version of...
David Jonathan Coffin, Christopher D. Clack
GECCO
2006
Springer
145views Optimization» more  GECCO 2006»
13 years 12 months ago
Immune anomaly detection enhanced with evolutionary paradigms
The paper presents an approach based on principles of immune systems to the anomaly detection problem. Flexibility and efficiency of the anomaly detection system are achieved by b...
Marek Ostaszewski, Franciszek Seredynski, Pascal B...
GECCO
2000
Springer
109views Optimization» more  GECCO 2000»
13 years 12 months ago
GP+Echo+Subsumption = Improved Problem Solving
Real-time, adaptive control is a difficult problem that can be addressed by EC architectures. We are interested in incorporating into an EC architecture some of the features that ...
William F. Punch, W. M. Rand
EUROGP
2008
Springer
13 years 10 months ago
Exposing a Bias Toward Short-Length Numbers in Grammatical Evolution
Many automatically-synthesized programs have, like their hand-made counterparts, numerical parameters that need to be set properly before they can show an acceptable performance. H...
Marco Antonio Montes de Oca
IJCAI
1993
13 years 9 months ago
Evolutionary Learning Strategy using Bug-Based Search
We introduce a new approach to GA (Genetic Algorithms) based problem solving. Earlier GAs did not contain local search (i.e. hill climbing) mechanisms, which led to optimization d...
Hitoshi Iba, Tetsuya Higuchi, Hugo de Garis, Taisu...