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Consensus of complex network systems and ergodicity of Markov chains

机译:复杂网络系统的共识和马尔可夫链的遍历性

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摘要

This study studies the consensus of multi-agent systems on time-varying network topologies. It is shown that this consensus reaching is equivalent to the corresponding weak ergodicity of the Markov process. A very mild sufficient condition of the consensus reaching that allows the communication among agents to be time-dependent and directed is obtained by estimating the Dobrushin coefficient of ergodicity. It is also shown that the notion of in-branching spanning tree plays a central role in the reaching of consensus. Moreover, sufficient conditions for (almost sure) consensus are presented for the case of time-varying networks.
机译:这项研究研究了多智能体系统在时变网络拓扑结构上的共识。结果表明,达成共识等同于马尔可夫过程的相应弱遍历性。通过估计Dobrushin的遍历性,可以获得一个非常温和的充分达成共识的条件,使代理之间的通信成为时间依赖性和有针对性的。还表明,分支生成树的概念在达成共识中起着核心作用。此外,对于时变网络,为(几乎确定的)共识提供了充分的条件。

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