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Information acquisition strategies for Bayesian network-based decision support

机译:基于贝叶斯网络决策支持的信息获取策略

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Determining how to utilize information acquisition resources optimally is a difficult task in the intelligence domain. Nevertheless, an intelligence analyst can expect little or no support for this from software tools today. In this paper, we describe a proof of concept implementation of a resource allocation mechanism for an intelligence analysis support system. The system uses a Bayesian network to structure intelligence requests, and the goal is to minimize the uncertainty of a variable of interest. A number of allocation strategies are discussed and evaluated through simulations.
机译:在智能领域,确定如何最佳地利用信息获取资源是一项艰巨的任务。尽管如此,情报分析师现在可能期望很少或根本不会从软件工具获得对此的支持。在本文中,我们描述了用于情报分析支持系统的资源分配机制的概念实现的证明。该系统使用贝叶斯网络构造智能请求,目标是最大程度地减少关注变量的不确定性。通过模拟讨论并评估了许多分配策略。

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