Paper
26 April 2018 Self-organization in multilayer network with adaptation mechanisms based on competition
Elena N. Pitsik, Vladimir V. Makarov, Vladimir O. Nedaivozov, Daniil V. Kirsanov, Mikhail V. Goremyko
Author Affiliations +
Abstract
The paper considers the phenomena of competition in multiplex network whose structure evolves corresponding to dynamics of it’s elements, forming closed loop of self-learning with the aim to reach the optimal topology. Numerical analysis of proposed model shows that it is possible to obtain scale-invariant structures for corresponding parameters as well as the structures with homogeneous distribution of connections in the layers. Revealed phenomena emerges as the consequence of the self-organization processes related to structure-dynamical selflearning based on homeostasis and homophily, as well as the result of the competition between the network’s layers for optimal topology. It was shown that in the mode of partial and cluster synchronization the network reaches scale-free topology of complex nature that is different from layer to layer. However, in the mode of global synchronization the homogeneous topologies on all layer of the network are observed. This phenomenon is tightly connected with the competitive processes that represent themselves as the natural mechanism of reaching the optimal topology of the links in variety of real-world systems.
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Elena N. Pitsik, Vladimir V. Makarov, Vladimir O. Nedaivozov, Daniil V. Kirsanov, and Mikhail V. Goremyko "Self-organization in multilayer network with adaptation mechanisms based on competition", Proc. SPIE 10717, Saratov Fall Meeting 2017: Laser Physics and Photonics XVIII; and Computational Biophysics and Analysis of Biomedical Data IV, 107172B (26 April 2018); https://doi.org/10.1117/12.2315120
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KEYWORDS
Systems modeling

Artificial intelligence

Brain

Numerical analysis

Oscillators

Robotics

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