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GECCO
2009
Springer
124views Optimization» more  GECCO 2009»
16 years 2 months ago
Three interconnected parameters for genetic algorithms
When an optimization problem is encoded using genetic algorithms, one must address issues of population size, crossover and mutation operators and probabilities, stopping criteria...
Pedro A. Diaz-Gomez, Dean F. Hougen
GECCO
2009
Springer
135views Optimization» more  GECCO 2009»
16 years 2 months ago
Steady-state ALPS for real-valued problems
The objectives of this paper are to describe a steady-state version of the Age-Layered Population Structure (ALPS) Evolutionary Algorithm (EA) and to compare it against other GAs ...
Gregory S. Hornby
GECCO
2009
Springer
305views Optimization» more  GECCO 2009»
16 years 2 months ago
Evolving competitive car controllers for racing games with neuroevolution
Modern computer games are at the same time an attractive application domain and an interesting testbed for the evolutionary computation techniques. In this paper we apply NeuroEvo...
Luigi Cardamone, Daniele Loiacono, Pier Luca Lanzi
GECCO
2009
Springer
122views Optimization» more  GECCO 2009»
16 years 2 months ago
Evolving symmetric and modular neural networks for distributed control
Problems such as the design of distributed controllers are characterized by modularity and symmetry. However, the symmetries useful for solving them are often difficult to determ...
Vinod K. Valsalam, Risto Miikkulainen
ICANNGA
2009
Springer
203views Algorithms» more  ICANNGA 2009»
16 years 2 months ago
NEAT in HyperNEAT Substituted with Genetic Programming
In this paper we present application of genetic programming (GP) [1] to evolution of indirect encoding of neural network weights. We compare usage of original HyperNEAT algorithm w...
Zdenek Buk, Jan Koutník, Miroslav Snorek