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» Introduction to genetic algorithms
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EC
2007
145views ECommerce» more  EC 2007»
15 years 6 months ago
Covariant Genetic Dynamics
We present a covariant form for the dynamics of a canonical GA of arbitrary cardinality, showing how each genetic operator can be uniquely represented by a mathematical object - a...
Chryssomalis Chryssomalakos, Christopher R. Stephe...
FGCS
2010
119views more  FGCS 2010»
15 years 5 months ago
Characterizing fault tolerance in genetic programming
Evolutionary Algorithms, including Genetic Programming (GP), are frequently employed to solve difficult real-life problems, which can require up to days or months of computation. ...
Daniel Lombraña Gonzalez, Francisco Fern&aa...
GECCO
2005
Springer
147views Optimization» more  GECCO 2005»
16 years 6 days ago
Unbiased tournament selection
Tournament selection is a popular form of selection which is commonly used with genetic algorithms, genetic programming and evolutionary programming. However, tournament selection...
Artem Sokolov, Darrell Whitley
PPSN
2004
Springer
16 years 1 days ago
Detecting and Pruning Introns for Faster Decision Tree Evolution
We show how the understandability and speed of genetic programming classification algorithms can be improved, without affecting the classification accuracy. By analyzing the dec...
Jeroen Eggermont, Joost N. Kok, Walter A. Kosters
GECCO
2003
Springer
119views Optimization» more  GECCO 2003»
15 years 12 months ago
Schema Analysis of Average Fitness in Multiplicative Landscape
By applying the schema theorem, we study the effects of crossover in Genetic Algorithms with the multiplicative fitness function. On this landscape, the analytical expression of ...
Hiroshi Furutani