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GECCO
2007
Springer
213views Optimization» more  GECCO 2007»
13 years 11 months ago
Aspects of adaptation in natural and artificial evolution
This work addresses selected aspects of natural evolution, especially of the field of population genetics, that are considered to be meaningful for algorithmic further development...
Michael Affenzeller, Stefan Wagner 0002, Stephan M...
GECCO
2006
Springer
215views Optimization» more  GECCO 2006»
13 years 11 months ago
A multi-chromosome approach to standard and embedded cartesian genetic programming
Embedded Cartesian Genetic Programming (ECGP) is an extension of Cartesian Genetic Programming (CGP) that can automatically acquire, evolve and re-use partial solutions in the for...
James Alfred Walker, Julian Francis Miller, Rachel...
GECCO
2009
Springer
162views Optimization» more  GECCO 2009»
13 years 5 months ago
Uncertainty handling CMA-ES for reinforcement learning
The covariance matrix adaptation evolution strategy (CMAES) has proven to be a powerful method for reinforcement learning (RL). Recently, the CMA-ES has been augmented with an ada...
Verena Heidrich-Meisner, Christian Igel
EOR
2006
135views more  EOR 2006»
13 years 7 months ago
Principles of scatter search
Scatter search is an evolutionary method that has been successfully applied to hard optimization problems. The fundamental concepts and principles of the method were first propose...
Rafael Martí, Manuel Laguna, Fred Glover
GECCO
2008
Springer
122views Optimization» more  GECCO 2008»
13 years 8 months ago
Varying portfolio construction of stocks using genetic network programming with control nodes
A new evolutionary method named “Genetic Network Programming with Control Nodes, GNPcn” has been proposed and applied to determine the timing of buying and selling stocks. GNP...
Etsushi Ohkawa, Yan Chen, Shingo Mabu, Kaoru Shima...