Minimum number of information gatherers to ensure full observability of a dynamic social network: A structural systems approach

S. Pequito, S. Kar, Antonio Pedro Aguiar
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引用次数: 14

Abstract

This paper studies the problem of identifying the minimum number of entities (agents), referred to as information gatherers, that are able to infer all the states in a dynamical social network. The information gatherers can be, for instance, service providers and the remaining agents the clients, each comprising several dynamic states associated with the services and personal information. The problem of identifying the minimum number of information gatherers can constitute a way to create coalitions to oversee the entire state of the system, and consequently the behavior of the agents in the social network. The dynamical social network is assumed to be modelled as a linear time-invariant system, and we will make use of the structural systems concept, i.e., by considering only the sparsity pattern (location of zeroes/non-zeroes) of the system coupling matrix. As a consequence, the design guarantees derived hold for almost all numerical parametric realizations of the system. In this paper, we show that this problem is NP-hard: in addition, we provide a reduction of the coalition problem to a minimum set covering problem that, in practice, leads to efficient (polynomial complexity) approximation schemes for solving the coalition problem with guaranteed optimality gaps. Finally, an example is provided which illustrates the analytical findings.
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确保动态社会网络完全可观察性的最小信息收集者数量:结构系统方法
本文研究了动态社会网络中能够推断所有状态的最小数量的实体(agent)的识别问题,这些实体(agent)被称为信息收集器。例如,信息收集者可以是服务提供者,其余的代理可以是客户,每个代理都包含与服务和个人信息相关联的几个动态状态。确定最小数量的信息收集者的问题可以构成一种创建联盟的方法,以监督系统的整个状态,从而监督社会网络中代理的行为。动态社会网络被假设为一个线性时不变系统,我们将利用结构系统概念,即只考虑系统耦合矩阵的稀疏模式(零/非零的位置)。因此,该设计保证了该系统几乎所有数值参数实现的推导性保持。在本文中,我们证明了这个问题是np困难的:此外,我们提供了一个将联盟问题简化为最小集覆盖问题的方法,在实践中,这导致了解决具有保证最优性间隙的联盟问题的有效(多项式复杂度)近似方案。最后,给出了一个例子来说明分析结果。
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