Abstract

According to modern USA defense doctrine, the future war will involve high mobility and operational tempo, a convergence of real and cyber battlespace, dependence on huge volumes of data from multiple heterogeneous sources, unpredictable enemy actions, and poorly defined borders of the operational theatre. As a consequence of these new characteristics, military decision makers at the operational and tactical levels need rapid, accurate, and consistent understanding of the battlefield situation, its dynamics, and potential future scenarios. A decision-support system for future war scenarios must be adaptive and exhibit some degree of learning as existing situations unfold and new situations emerge. This paper proposes a novel approach for analysis of battlespace situations based on dynamic cases. The approach integrates two core technologies developed earlier by the authors: real-time temporal event correlation (EC) and case-based reasoning (CBR).

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