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CEC
2005
IEEE
16 years 1 days ago
A hybrid approach to parameter tuning in genetic algorithms
Abstract- Choosing the best parameter setting is a wellknown important and challenging task in Evolutionary Algorithms (EAs). As one of the earliest parameter tuning techniques, th...
Bo Yuan, Marcus Gallagher
GECCO
2009
Springer
132views Optimization» more  GECCO 2009»
16 years 29 days ago
Bringing evolutionary computation to industrial applications with guide
Evolutionary Computation is an exciting research field with the power to assist researchers in the task of solving hard optimization problems (i.e., problems where the exploitabl...
Luís Da Costa, Marc Schoenauer
GECCO
2006
Springer
213views Optimization» more  GECCO 2006»
15 years 10 months ago
Evolutionary unit testing of object-oriented software using strongly-typed genetic programming
Evolutionary algorithms have successfully been applied to software testing. Not only approaches that search for numeric test data for procedural test objects have been investigate...
Stefan Wappler, Joachim Wegener
GECCO
2007
Springer
163views Optimization» more  GECCO 2007»
16 years 17 days ago
Action-selection and crossover strategies for self-modeling machines
In previous work [7] a computational framework was demonstrated that employs evolutionary algorithms to automatically model a given system. This is accomplished by alternating the...
Josh C. Bongard
CIKM
2007
Springer
16 years 17 days ago
Randomized metric induction and evolutionary conceptual clustering for semantic knowledge bases
We present an evolutionary clustering method which can be applied to multi-relational knowledge bases storing resource annotations expressed in the standard languages for the Sema...
Nicola Fanizzi, Claudia d'Amato, Floriana Esposito