Preprint
Article

Complex Network Formation as Antagonistic Game: Numerical Modeling

This version is not peer-reviewed.

Submitted:

11 July 2022

Posted:

21 July 2022

You are already at the latest version

A peer-reviewed article of this preprint also exists.

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
Subject: 
Computer Science and Mathematics  -   Mathematics
Copyright: This open access article is published under a Creative Commons CC BY 4.0 license, which permit the free download, distribution, and reuse, provided that the author and preprint are cited in any reuse.

Altmetrics

Downloads

151

Views

120

Comments

0

Subscription

Notify me about updates to this article or when a peer-reviewed version is published.

Email

Prerpints.org logo

Preprints.org is a free preprint server supported by MDPI in Basel, Switzerland.

Subscribe

© 2025 MDPI (Basel, Switzerland) unless otherwise stated