态势评估中的问题与挑战(2级融合)

Erik Blasch, I. Kadar, J. Salerno, M. Kokar, S. Das, G. Powell, D. Corkill, E. Ruspini
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引用次数: 142

摘要

摘要:态势评估(Situation assessment, SA)涉及实体之间关系的推导,如对象状态的聚合(即分类和位置)。虽然在信息融合和人因方面的文献中对情景分析已经有了一定的认识,但在知识表示和推理方法上仍然存在一些开放性的问题。例如,虽然在感兴趣的区域收集了大量数据,但如何将这些信息呈现给注意力受限的用户?信息过载会影响认知推理,因此需要一种实用的知识表示解决方案来实现有效和高效的情景理解。在本文中,我们提出了与2级信息融合(态势评估)相关的问题,包括:(1)用户感知和感知推理表示,(2)知识发现过程模型,(3)关于关系的程序与逻辑推理,(4)通过性能指标进行用户融合交互,以及(5)句法和语义表示。虽然明确的结论不是本文的目的,但提出了许多关键问题,以便描述未来成功的知识表示、呈现和情况评估推理策略。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Issues and Challenges in Situation Assessment (Level 2 Fusion)
Abstract : Situation assessment (SA) involves deriving relations among entities, e.g., the aggregation of object states (i.e., classification and location). While SA has been recognized in the information fusion and human factors literature, there still exist open questions regarding knowledge representation and reasoning methods to afford SA. For instance, while lots of data is collected over a region of interest, how does this information get presented to an attention constrained user? The information overload can deteriorate cognitive reasoning so a pragmatic solution to knowledge representation is needed for effective and efficient situation understanding. In this paper, we present issues associated with Level 2 Information Fusion (Situation Assessment) including: (1) user perception and perceptual reasoning representation, (2) knowledge discovery process models, (3) procedural versus logical reasoning about relationships, (4) userfusion interaction through performance metrics, and (5) syntactic and semantic representations. While a definitive conclusion is not the aim of the paper, many critical issues are proposed in order to characterize future successful strategies for knowledge representation, presentation, and reasoning for situation assessment.
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