Algorithms: their complexity and efficiency
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Genetic algorithm hardness. Selection and convergence. Classifier systems. Coding and representation. Framework issues. Variation and recombination.
Foundations issues revisited. Modeling genetic algorithms. Deception and the building block hypothesis. Convergence and genetic diversity. Genetic operators and their analysis. Machine learning.
Handbook of theoretical computer science
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Type: Book
"Network science is an emerging field of study that encompasses mathematics, computer science, physics, and engineering. An important issue in the study of complex networks is to understand the collective behavior of the elements of these networks. Although the results from grap…
