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GECCO
2003
Springer
117views Optimization» more  GECCO 2003»
15 years 3 months ago
A Method for Handling Numerical Attributes in GA-Based Inductive Concept Learners
This paper proposes a method for dealing with numerical attributes in inductive concept learning systems based on genetic algorithms. The method uses constraints for restricting th...
Federico Divina, Maarten Keijzer, Elena Marchiori
CONTEXT
2001
Springer
15 years 2 months ago
Learning Appropriate Contexts
Genetic Programming is extended so that the solutions being evolved do so in the context of local domains within the total problem domain. This produces a situation where different...
Bruce Edmonds
PPSN
1998
Springer
15 years 1 months ago
Methods to Evolve Legal Phenotypes
Many optimization problems require the satisfaction of constraints in addition to their objectives. When using an evolutionary algorithm to solve such problems, these constraints c...
Tina Yu, Peter J. Bentley
EUROGP
2007
Springer
143views Optimization» more  EUROGP 2007»
15 years 1 months ago
Confidence Intervals for Computational Effort Comparisons
Abstract. When researchers make alterations to the genetic programming algorithm they almost invariably wish to measure the change in performance of the evolutionary system. No one...
Matthew Walker, Howard Edwards, Chris H. Messom
GECCO
2000
Springer
123views Optimization» more  GECCO 2000»
15 years 1 months ago
Genomic computing: explanatory modelling for functional genomics
Many newly discovered genes are of unknown function. DNA microarrays are a method for determining the expression levels of all genes in an organism for which a complete genome seq...
Richard J. Gilbert, Jem J. Rowland, Douglas B. Kel...