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» On the practical genetic algorithms
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GECCO
2008
Springer
144views Optimization» more  GECCO 2008»
15 years 7 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
201views Optimization» more  GECCO 2008»
15 years 7 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
PODC
2003
ACM
15 years 12 months ago
Geometric ad-hoc routing: of theory and practice
All too often a seemingly insurmountable divide between theory and practice can be witnessed. In this paper we try to contribute to narrowing this gap in the field of ad-hoc rout...
Fabian Kuhn, Roger Wattenhofer, Yan Zhang, Aaron Z...
IJCAI
1997
15 years 8 months ago
Is Nonparametric Learning Practical in Very High Dimensional Spaces?
Many of the challenges faced by the £eld of Computational Intelligence in building intelligent agents, involve determining mappings between numerous and varied sensor inputs and ...
Gregory Z. Grudic, Peter D. Lawrence
CEC
2009
IEEE
16 years 1 months ago
Evolving novel image features using Genetic Programming-based image transforms
— In this paper, we use Genetic Programming (GP) to define a set of transforms on the space of greyscale images. The motivation is to allow an evolutionary algorithm means of tr...
Taras Kowaliw, Wolfgang Banzhaf, Nawwaf N. Kharma,...