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» Adapting binary fitness functions in Genetic Algorithms
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42
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ICEC
1994
37views more  ICEC 1994»
14 years 11 months ago
A Method for Utilizing Diploid/Dominance in Genetic Search
homologous alleles seemingly compete prior to manifestation in the observed phenotype, will be referred to as sub-phenotype interaction.A method is proposed for implementing diploi...
F. Greene
ICGA
1993
157views Optimization» more  ICGA 1993»
14 years 11 months ago
Optimal Interaction of Mutation and Crossover in the Breeder Genetic Algorithm
The dynamic behavior of mutation and crossover is investigated with the Breeder Genetic Algorithm. The main emphasis is on binary functions. The genetic operators are compared nea...
Heinz Mühlenbein, Dirk Schlierkamp-Voosen
GECCO
2006
Springer
152views Optimization» more  GECCO 2006»
15 years 1 months ago
Strong recombination, weak selection, and mutation
We show that there are unimodal fitness functions and genetic algorithm (GA) parameter settings where the GA, when initialized with a random population, will not move close to the...
Alden H. Wright, J. Neal Richter
99
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EUROGP
2007
Springer
126views Optimization» more  EUROGP 2007»
15 years 1 months ago
Training Binary GP Classifiers Efficiently: A Pareto-coevolutionary Approach
The conversion and extension of the Incremental Pareto-Coevolution Archive algorithm (IPCA) into the domain of Genetic Programming classification is presented. In particular, the ...
Michal Lemczyk, Malcolm I. Heywood
GECCO
2006
Springer
156views Optimization» more  GECCO 2006»
15 years 1 months ago
Improving GP classifier generalization using a cluster separation metric
Genetic Programming offers freedom in the definition of the cost function that is unparalleled among supervised learning algorithms. However, this freedom goes largely unexploited...
Ashley George, Malcolm I. Heywood