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GECCO
2009
Springer
103views Optimization» more  GECCO 2009»
14 years 2 months ago
Why evolution is not a good paradigm for program induction: a critique of genetic programming
We revisit the roots of Genetic Programming (i.e. Natural Evolution), and conclude that the mechanisms of the process of evolution (i.e. selection, inheritance and variation) are ...
John R. Woodward, Ruibin Bai
GECCO
2007
Springer
130views Optimization» more  GECCO 2007»
14 years 1 months ago
Variable discrimination of crossover versus mutation using parameterized modular structure
Recent work has provided functions that can be used to prove a principled distinction between the capabilities of mutation-based and crossover-based algorithms. However, prior fun...
Rob Mills, Richard A. Watson
GECCO
2008
Springer
117views Optimization» more  GECCO 2008»
13 years 8 months ago
CrossNet: a framework for crossover with network-based chromosomal representations
We propose a new class of crossover operators for genetic algorithms (CrossNet) which use a network-based (or graphbased) chromosomal representation. We designed CrossNet with the...
Forrest Stonedahl, William Rand, Uri Wilensky
EC
2006
195views ECommerce» more  EC 2006»
13 years 7 months ago
Automated Global Structure Extraction for Effective Local Building Block Processing in XCS
Learning Classifier Systems (LCSs), such as the accuracy-based XCS, evolve distributed problem solutions represented by a population of rules. During evolution, features are speci...
Martin V. Butz, Martin Pelikan, Xavier Llorà...
GECCO
2011
Springer
248views Optimization» more  GECCO 2011»
12 years 11 months ago
Size-based tournaments for node selection
In genetic programming, the reproductive operators of crossover and mutation both require the selection of nodes from the reproducing individuals. Both unbiased random selection a...
Thomas Helmuth, Lee Spector, Brian Martin