Abstract
Modern decision making challenges the human capacity to reason in an environment of uncertainty, imprecision, and incompleteness of information. Atop the uncertainty, ranking in the presence of multiple criteria, multiple agents, and heterogeneous sources of information is often the main task to accomplish by the analysts in the Intelligence Community (IC). Soft metrics are attributes of decision criteria that cannot be expressed numerically. These metrics are at the core of a computational engine that is perception-based, with computational 'atoms' expressed in natural language (NL). The soft metrics approach as a basis for natural language-based computing contributes to fast analyses and an efficient use of human resources in contemporary decision making such as: intelligence data analysis, the Global Strike (target pairing), risk analysis, threat assessment, strategic interactions, conflict analysis, and the strategic deterrence assessment.
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