论文标题
影响在异质多重线性阈值模型中传播
Influence Spread in the Heterogeneous Multiplex Linear Threshold Model
论文作者
论文摘要
线性阈值模型（LTM）已用于研究通过协议中的一种基因间感应方式和代理定义的单层网络的扩散。我们定义和分析了异质的多重LTM，以研究在多层网络上的扩散，每个层代表不同的传感方式和方案中异质性的代理。协议旨在将信号与不同层区分开：如果在$ m $ layers的每一个$ a $ a $ a las intive中，代理会变得有效。我们专注于协议，或者当$ a = 1 $和协议时，以及当$ a = m $时，哪些模型代理分别是最不容易激活的。我们开发理论和算法来计算任何最初活性药物的稳态扩散的大小，并分析杰出的感应方式，网络结构和异质性的作用。我们展示了异质性如何管理对投入的敏感性和对干扰鲁棒性的敏感性之间的张力。
The linear threshold model (LTM) has been used to study spread on single-layer networks defined by one inter-agent sensing modality and agents homogeneous in protocol. We define and analyze the heterogeneous multiplex LTM to study spread on multi-layer networks with each layer representing a different sensing modality and agents heterogeneous in protocol. Protocols are designed to distinguish signals from different layers: an agent becomes active if a sufficient number of its neighbors in each of any $a$ of the $m$ layers is active. We focus on Protocol OR, when $a=1$, and Protocol AND, when $a=m$, which model agents that are most and least readily activated, respectively. We develop theory and algorithms to compute the size of the spread at steady state for any set of initially active agents and to analyze the role of distinguished sensing modalities, network structure, and heterogeneity. We show how heterogeneity manages the tension in spreading dynamics between sensitivity to inputs and robustness to disturbances.
