Submitted:
11 July 2022
Posted:
21 July 2022
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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).
Keywords:
Graph complexity
; antagonistic game theory
; partition networks
; neural networks
; numeric modellng
; Nash equilibrium
; Neumann equilibrium
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