This paper models the cyber-social system as a cyber-network of agents monitoring states of individuals in a social network. The state of each individual is represented by a social node, and the interactions among individuals are represented by a social link. In the cyber-network, each node represents an agent, and the links represent information sharing among agents. The agents make an observation of social states and perform distributed inference. In this direction, the contribution of this paper is threefold: First, a novel distributed inference protocol is proposed that makes no assumption on the rank of the underlying social system. This is significant as most protocols in the literature only work on full-rank systems. Second, a novel agent classification is developed, where it is shown that the connectivity requirement of the cyber-network differs for each type. This is particularly important in finding the minimal number of observations and minimal connectivity of the cyber-network as the next contribution. Third, the cost-optimal design of the cyber-network constraint with distributed observability is addressed. This problem is subdivided into sensing cost optimization and networking cost optimization, where both are claimed to be NP-hard. We solve both the problems for certain types of social networks and find polynomial-order solutions.

中文翻译：

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网络社会系统：建模，推理和最佳设计

本文将网络社交系统建模为监视社交网络中个人状态的代理人网络。每个人的状态由一个社交节点表示，而个人之间的交互则由一个社交链接表示。在网络中，每个节点代表一个代理，链接代表代理之间的信息共享。代理对社会状态进行观察并执行分布式推理。在这个方向上，本文的贡献是三方面的：首先，提出了一种新的分布式推理协议，该协议不对底层社会系统的排名进行任何假设。这很重要，因为文献中的大多数协议仅适用于全等级系统。其次，开发了一种新颖的代理商分类，其中显示了每种类型的网络网络的连通性要求都不同。在找到最少的观测值和最小的网络连接性方面，这尤其重要，这是下一个贡献。第三，解决了具有分布式可观察性的网络约束的成本最优设计。该问题可细分为感知成本优化和网络成本优化，其中两者均被认为是NP难的。我们针对某些类型的社交网络解决了这两个问题，并找到了多项式阶解。解决了具有分布式可观察性的网络约束的成本优化设计。该问题可细分为感知成本优化和网络成本优化，其中两者均被认为是NP难的。我们针对某些类型的社交网络解决了这两个问题，并找到了多项式阶解。解决了具有分布式可观察性的网络约束的成本优化设计。该问题可细分为感知成本优化和网络成本优化，这两者都被认为是NP难的。我们针对某些类型的社交网络解决了这两个问题，并找到了多项式阶解。