Abstract

Complex problems such as analysis of military situation assessment, homeland defense, diagnosis of the health of complex systems, medical diagnosis, and environmental monitoring require the ability to utilize a wide variety of data such as signals, images, textual information, and scalar data. The rapid evolution of micro-scale sensors, wideband communications, and microprocessors enables the collection and dissemination of huge amounts of data to be provided to a human analyst. Unfortunately, the analyst cannot directly understand nor process the data. Instead, analysts reason about high-level abstractions via language. A challenge exists to decompose general problems into detailed models that link to specific types of data (viz., problem centered decomposition) and to compose data into meaningful relationships to assist the understanding of semantic representations of abstract concepts. This paper discusses the challenge of problem-centered analysis (including problem centered decomposition and problem centered composition) and describes our efforts to develop cognitive aids to assist the analysis process for improved understanding of complex problems.

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