The concept of information gain has been adopted as tool to study the effectiveness of population-based optimizers; using this approach, it is possible to infer convergence properties for population-based optimizers. The experimental results have shown characteristic phase transition between exploration and exploitation phase during the evolutionary process and, moreover, the evidence that gain maximization offers a robust theoretical framework to study the convergence of stochastic optimizers.
Titolo: | Entropic Divergence for Population Based Optimization Algorithms |
Autori interni: | |
Data di pubblicazione: | 2010 |
Handle: | http://hdl.handle.net/20.500.11769/74057 |
ISBN: | 978-1-4244-6909-3 |
Appare nelle tipologie: | 4.1 Contributo in Atti di convegno |
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