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Reasoning About Trust and Belief Change on a Social Network: A Formal Approach

机译:关于社交网络上信任和信念变化的推理:一种正式方法

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One important aspect of trust is the following: when a trusted source reports some new information, then we are likely to believe that the new information is true. As such, the notion of trust is closely connected to the notion of belief change. In this paper, we demonstrate how a formal model of trust developed in the Artificial Intelligence community can be used to model the dynamics of belief on a social network. We use a formal model to capture the preceived areas of expertise of each agent, and we introduce a logical operator to determine how beliefs change following reported information. Significantly, the trust held in another agent is not determined solely by individual expertise; the extent to which an agent is trusted is also influenced by social relationships between agents. We prove a number of formal properties, and demonstrate that our approach can actually model a wide range of practical trust problems involving social agents. This work is largely foundational, and it connects two different research communities. In particular, this work illustrates how fundamentally logic-based models of reasoning can be applied to solve problems related to trust on social networks.
机译:信任的一个重要方面如下:当一个受信任的源报告了一些新信息时,我们很可能会认为这些新信息是真实的。因此,信任的概念与信念改变的概念紧密相关。在本文中,我们演示了如何使用人工智能社区开发的正式信任模型来对社交网络上的信念动态进行建模。我们使用正式的模型来捕获每个代理的专业知识领域,并引入逻辑运算符来确定在报告的信息后信念如何变化。重要的是,在另一个代理商中持有的信托并不完全由个人的专业知识决定。代理商受信任的程度也受代理商之间社会关系的影响。我们证明了许多形式上的特性,并证明了我们的方法实际上可以对涉及社会代理人的各种实际信任问题进行建模。这项工作在很大程度上是基础性的,它将两个不同的研究社区联系在一起。特别是,这项工作说明了如何从根本上将基于逻辑的推理模型应用于解决与社交网络信任有关的问题。

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