鲁棒多智能体网络随机规则图的分散形成

A. Y. Yazicioglu, M. Egerstedt, J. Shamma
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引用次数: 7

摘要

多智能体网络通常通过交互图建模,其中节点表示智能体,边表示相应智能体之间的直接交互。交互图对网络系统的鲁棒性有重要影响。鲁棒图的一类是随机正则图。本文提出了一种局部适用的重构方案,通过自组织构造随机正则图。对于任何连通的初始图,该方案在保持连通性和平均度的同时,最小化度差并使链路随机化。因此,如果初始图的平均度为整数,则随着时间趋于无穷,连通正则图均匀随机实现。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Decentralized formation of random regular graphs for robust multi-agent networks
Multi-agent networks are often modeled via interaction graphs, where the nodes represent the agents and the edges denote direct interactions between the corresponding agents. Interaction graphs have significant impact on the robustness of networked systems. One family of robust graphs is the random regular graphs. In this paper, we present a locally applicable reconfiguration scheme to build random regular graphs through self-organization. For any connected initial graph, the proposed scheme maintains connectivity and the average degree while minimizing the degree differences and randomizing the links. As such, if the average degree of the initial graph is an integer, then connected regular graphs are realized uniformly at random as time goes to infinity.
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