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3. Theoretical overview: why and how does it work?
The big question is when and how to make effective use of AEs, since they are fairly complex optimization algorithms to implement and relatively costly in terms of computing time (as we've said, the "black box" approach is unreasonable). The answer to this question is not straightforward. However, numerous theoretical and experimental analyses provide some clues as to when the use of an AE is justified or can make a contribution in comparison or collaboration with conventional techniques.
Historically, schema theory represents the first "theory" of global convergence in genetic algorithms; in fact, it is an extremely simplified model of the behavior of an AE
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Theoretical overview: why and how does it work?
Model extensions
Bibliography
Software tools
Inspyred, a library of bioinspired algorithms in Python language
https://pythonhosted.org/inspyred/
GAlib - C++ Genetic Algorithms Library
https://sourceforge.net/projects/galib/
Matlab Global Optimization...
Websites
Association Évolution artificielle
It brings together French researchers in this field and organizes international conferences (EA), conferences and schools.
SIGEVO, Special Interest Group on Genetic and Evolutionary Computation
Events
ACM Genetic and Evolutionary Computation Conference (GECCO)
https://dl.acm.org/conference/gecco
IEEE Congress on Evolutionary Computation (CEC)
EvoStar
Co-location of four international...
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