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GECCO
2005
Springer
177views Optimization» more  GECCO 2005»
15 years 3 months ago
Evolving next generation signal compression and reconstruction transforms via genetic algorithms
Ongoing research has established a new methodology for using genetic algorithms [2] to evolve forward and inverse transforms that significantly reduce quantization error in recons...
Frank W. Moore, Patrick Marshall
GECCO
2006
Springer
143views Optimization» more  GECCO 2006»
15 years 1 months ago
Heterogeneous cooperative coevolution: strategies of integration between GP and GA
Cooperative coevolution has proven to be a promising technique for solving complex combinatorial optimization problems. In this paper, we present four different strategies which i...
Leonardo Vanneschi, Giancarlo Mauri, Andrea Valsec...
EUROGP
2007
Springer
135views Optimization» more  EUROGP 2007»
15 years 3 months ago
A Grammatical Genetic Programming Approach to Modularity in Genetic Algorithms
The ability of Genetic Programming to scale to problems of increasing difficulty operates on the premise that it is possible to capture regularities that exist in a problem environ...
Erik Hemberg, Conor Gilligan, Michael O'Neill, Ant...
GECCO
2005
Springer
163views Optimization» more  GECCO 2005»
15 years 3 months ago
Memory-based immigrants for genetic algorithms in dynamic environments
Investigating and enhancing the performance of genetic algorithms in dynamic environments have attracted a growing interest from the community of genetic algorithms in recent year...
Shengxiang Yang
IWINAC
2005
Springer
15 years 3 months ago
The Allele Meta-model - Developing a Common Language for Genetic Algorithms
Abstract. Due to the lot of different Genetic Algorithm variants, encodings, and attacked problems, very little general theory is available to explain the internal functioning of ...
Stefan Wagner 0002, Michael Affenzeller