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» Evolving Crossover Operators for Function Optimization
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EUROGP
2006
Springer
138views Optimization» more  EUROGP 2006»
13 years 8 months ago
Evolving Crossover Operators for Function Optimization
Abstract. A new model for evolving crossover operators for evolutionary function optimization is proposed in this paper. The model is a hybrid technique that combines a Genetic Pro...
Laura Diosan, Mihai Oltean
EPS
1998
Springer
13 years 8 months ago
Dual Network Representation Applied to the Evolution of Neural Controllers
This paperpresentsa new approachto the evolutionof neuralnetworks. A linear chromosome combined with a grid-based representation of the network and a new crossover operator allow t...
João Carlos Figueira Pujol, Riccardo Poli
GECCO
2010
Springer
129views Optimization» more  GECCO 2010»
13 years 9 months ago
A probabilistic functional crossover operator for genetic programming
The original mechanism by which evolutionary algorithms were to solve problems was to allow for the gradual discovery of sub-solutions to sub-problems, and the automated combinati...
Josh C. Bongard
EUROGP
2007
Springer
144views Optimization» more  EUROGP 2007»
13 years 10 months ago
Fitness Landscape Analysis and Image Filter Evolution Using Functional-Level CGP
This work analyzes fitness landscapes for the image filter design problem approached using functional-level Cartesian Genetic Programming. Smoothness and ruggedness of fitness l...
Karel Slaný, Lukás Sekanina
GECCO
2006
Springer
195views Optimization» more  GECCO 2006»
13 years 8 months ago
Studying XCS/BOA learning in Boolean functions: structure encoding and random Boolean functions
Recently, studies with the XCS classifier system on Boolean functions have shown that in certain types of functions simple crossover operators can lead to disruption and, conseque...
Martin V. Butz, Martin Pelikan