Navigating temporal networks
Navigating temporal networks
复制标题
导航时间网络
DOI：
10.1016/j.physa.2018.09.036
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发表时间：
2019
期刊：
影响因子：
--
通讯作者：
Holme Petter
中科院分区：
文献类型：
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作者：
Lee Sang Hoon;Holme Petter
图上的导航是一个在图上行走的智能体如何在有限的图信息的情况下从源到达目标的问题。信息和利用它的方式可能会有所不同。在本文中，我们研究导航的时间网络，我们有明确的信息的时间的互动，而不仅仅是谁与谁互动。我们对比了一种贪婪的导航-代理遵循的路径，将在过去工作得很好-与两个战略，不利用额外的信息。我们测试这些经验的时间网络数据集。贪婪导航比参考策略更快更可靠地找到目标，这意味着可以利用真实的时间网络中的相关性。我们发现，拓扑结构和时间结构影响导航。
Navigation on graphs is the problem how an agent walking on the graph can get from a source to a target with limited information about the graph. The information and the way to exploit it can vary. In this paper, we study navigation on temporal networks—networks where we have explicit information about the time of the interaction, not only who interacts with whom. We contrast a type of greedy navigation – where agents follow paths that would have worked well in the past – with two strategies that do not exploit the additional information. We test these on empirical temporal network data sets. The greedy navigation finds the targets faster and more reliably than the reference strategies, meaning that there are correlations in the real temporal networks that can be exploited. We find that both topological and temporal structures affect the navigation.