3. Theoretical overview: why and how does it work?
The big question is when and how to use AEs effectively, since they are optimization algorithms that are quite complex to implement and relatively costly in terms of computing time (as mentioned above, the "black box" approach is not recommended). The answer to this question is not simple. However, numerous theoretical and experimental analyses provide some insights into when the use of an AE is justified or can offer advantages in comparison with or in combination with conventional techniques.
Historically, pattern theory represents the first global convergence theory for genetic algorithms; it is in fact 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 bio-inspired algorithms in Python
https://pythonhosted.org/inspyred/
GAlib - C++ Genetic Algorithms Library
https://sourceforge.net/projects/galib/
Matlab Global Optimization...
Websites
Artificial Evolution Association
It brings together French researchers in this field and organizes international conferences (EA), workshops, 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)
https://en.wikipedia.org/wiki/IEEE_Congress_on_Evolutionary_Computation
...
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