Bocharov, P.; Goryashko, A. Complex Network Formation as Antagonistic Game: Numerical Modeling. Preprints2022, 2022070324. https://doi.org/10.20944/preprints202207.0324.v1
APA Style
Bocharov, P., & Goryashko, A. (2022). Complex Network Formation as Antagonistic Game: Numerical Modeling. Preprints. https://doi.org/10.20944/preprints202207.0324.v1
Chicago/Turabian Style
Bocharov, P. and Alexander Goryashko. 2022 "Complex Network Formation as Antagonistic Game: Numerical Modeling" Preprints. https://doi.org/10.20944/preprints202207.0324.v1
Abstract
The basic challenges of this work are twofold: demonstrating the dependence between the functional and topological qualities of partition networks and finding the simplest—with respect to algorithmic complexity—network elements. The study of these problems is based on finding the solution to an appropriate antagonistic vertex game. The results of the numerical simulations of antagonistic partition games demonstrate that the winner’s graphs are “almost always” dense and hyperenergetic compared to the loser’s graphs. These observations reveal that successful evolutionary mechanisms can be realized, in principle, by the simplest objects (such as viruses).
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
