基于贝叶斯网络的决策支持信息获取策略

R. Johansson, Christian Mårtenson
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引用次数: 4

摘要

如何最优地利用信息获取资源是情报领域的一个难题。然而,情报分析人员可以期望很少或根本没有软件工具对此提供支持。在本文中,我们描述了一个智能分析支持系统的资源分配机制的概念验证实现。该系统使用贝叶斯网络来构建智能请求,目标是最小化感兴趣变量的不确定性。通过仿真,讨论并评价了多种分配策略。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Information acquisition strategies for Bayesian network-based decision support
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.
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