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GECCO
2004
Springer
13 years 10 months ago
Introducing Subchromosome Representations to the Linkage Learning Genetic Algorithm
This paper introduces subchromosome representations to the linkage learning genetic algorithm (LLGA). The subchromosome representation is utilized for effectively lowering the num...
Ying-Ping Chen, David E. Goldberg
CEC
2005
IEEE
13 years 10 months ago
Linear genetic programming using a compressed genotype representation
This paper presents a modularization strategy for linear genetic programming (GP) based on a substring compression/substitution scheme. The purpose of this substitution scheme is t...
Johan Parent, Ann Nowé, Kris Steenhaut, Ann...
GPEM
2002
95views more  GPEM 2002»
13 years 4 months ago
On Appropriate Adaptation Levels for the Learning of Gene Linkage
A number of algorithms have been proposed aimed at tackling the problem of learning "Gene Linkage" within the context of genetic optimisation, that is to say, the problem...
James Smith
KDD
1995
ACM
112views Data Mining» more  KDD 1995»
13 years 8 months ago
Learning First Order Logic Rules with a Genetic Algorithm
This paper introduces a newalgorithm called SIAO1 for learning first order logic rules withgenetic algorithms. SIAO1uses the covering principle developed in AQwhereseed examplesar...
Sébastien Augier, Gilles Venturini, Yves Ko...
GECCO
2000
Springer
138views Optimization» more  GECCO 2000»
13 years 8 months ago
Time Complexity of genetic algorithms on exponentially scaled problems
This paper gives a theoretical and empirical analysis of the time complexity of genetic algorithms (GAs) on problems with exponentially scaled building blocks. It is important to ...
Fernando G. Lobo, David E. Goldberg, Martin Pelika...