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GECCO
2008
Springer
144views Optimization» more  GECCO 2008»
14 years 11 months ago
Maintaining diversity through adaptive selection, crossover and mutation
This paper presents an Adaptive Genetic Algorithm (AGA) where selection pressure, crossover and mutation probabilities are adapted according to population diversity statistics. Th...
Brian McGinley, Fearghal Morgan, Colm O'Riordan
GECCO
2008
Springer
278views Optimization» more  GECCO 2008»
14 years 11 months ago
Elitism reduces bloat in genetic programming
Elitism is commonly used in generational GP to ensure that the best individuals discovered in a generation are not lost, and are made available for possible further improvements t...
Riccardo Poli, Nicholas Freitag McPhee, Leonardo V...
GECCO
2008
Springer
201views Optimization» more  GECCO 2008»
14 years 11 months ago
Advanced techniques for the creation and propagation of modules in cartesian genetic programming
The choice of an appropriate hardware representation model is key to successful evolution of digital circuits. One of the most popular models is cartesian genetic programming, whi...
Paul Kaufmann, Marco Platzner
EPS
1998
Springer
15 years 2 months ago
Acquisition of General Adaptive Features by Evolution
We investigate the following question. Do populations of evolving agents adapt only to their recent environment or do general adaptive features appear over time? We find statistica...
Dan Ashlock, John E. Mayfield
FLAIRS
2008
15 years 3 days ago
Genetic Approach for Optimizing Ensembles of Classifiers
An ensemble of classifiers is a set of classifiers whose predictions are combined in some way to classify new instances. Early research has shown that, in general, an ensemble of ...
Francisco Javier Ordóñez, Agapito Le...