Situation assessment via Bayesian belief networks

Proceedings of the Fifth International Conference on Information Fusion. FUSION 2002. (IEEE Cat.No.02EX5997) Pub Date : 2002-07-08 DOI:10.1109/ICIF.2002.1021218

S. Das, R. Grey, P. Gonsalves

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引用次数: 72

Abstract

We present here an approach to battlefield situation assessment based on a level 2 fusion processing of incoming information via probabilistic Bayesian Belief Network technology. A belief network (BN) can be thought of as a graphical program script representing causal relationships among various battlefield concepts represented as nodes to which observed significant events are posted as evidence. In our approach, each BN can be constructed in real-time from a library of smaller component-like BNs to assess a specific high-level situation or address mission-specific high-level intelligence requirements. Furthermore, by distributing components of a BN across a set of networked computers, we enhance inferencing efficiency and allow computation at various levels of abstraction suitable for military hierarchical organizations. We demonstrate them effectiveness of our approach by modeling the situation assessment tasks in the context of a battlefield scenario and implementing on our in-house software engine BNet 2000.

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基于贝叶斯信念网络的态势评估

本文提出了一种基于概率贝叶斯信念网络技术对传入信息进行2级融合处理的战场态势评估方法。信念网络(BN)可以被认为是一个图形程序脚本，表示各种战场概念之间的因果关系，这些概念表示为节点，观察到的重大事件被作为证据贴在节点上。在我们的方法中，每个BN可以从较小的组件库(如BN)实时构建，以评估特定的高级情况或解决特定任务的高级情报需求。此外，通过将BN的组件分布在一组网络计算机上，我们提高了推理效率，并允许在适合军事分层组织的各种抽象级别上进行计算。我们通过在战场场景的背景下对态势评估任务进行建模，并在我们的内部软件引擎BNet 2000上实现，来证明我们方法的有效性。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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Proceedings of the Fifth International Conference on Information Fusion. FUSION 2002. (IEEE Cat.No.02EX5997)

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