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Title: | Evolutionary algorithms dynamics and its hidden complex network structures |
Author: | Zelinka, Ivan; Davendra, Donald David; Lampinen, Jouni; Šenkeřík, Roman; Pluháček, Michal |
Document type: | Peer-reviewed article (English) |
Source document: | Proceedings of the 2014 IEEE Congress on Evolutionary Computation, CEC 2014. 2014, p. 3246-3251 |
ISBN: | 978-1-4799-1488-3 |
DOI: | https://doi.org/10.1109/CEC.2014.6900441 |
Abstract: | In this participation, we are continuing to show mutual intersection of two completely different areas of research: Complex networks and evolutionary computation. Large-scale networks, exhibiting complex patterns of interaction amongst vertices exist in both nature and man-made systems (i.e., communication networks, genetic pathways, ecological or economical networks, social networks, networks of various scientific collaboration etc.) and are a part of our daily life. We demonstrate that dynamics of evolutionary algorithms, that are based on Darwin theory of evolution and Mendel theory of genetic heritage, can be also visualized as complex networks. Such network can be then analyzed by means of classical tools of complex networks science. Results presented here are currently numerical demonstration rather than theoretical mathematical proofs. We open question whether evolutionary algorithms really create complex network structures and whether this knowledge can be successfully used like feedback for control of evolutionary dynamics and its improvement in order to increase the performance of evolutionary algorithms. © 2014 IEEE. |
Full text: | https://ieeexplore.ieee.org/document/6900441 |
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