Authors
Jobst Landgrebe
State University of New York (SUNY)
David Limbaugh
State University of New York (SUNY)
Barry Smith
State University of New York, Buffalo
1 more
Abstract
The term ‘intelligence’ as used in this paper refers to items of knowledge collected for the sake of assessing and maintaining national security. The intelligence community (IC) of the United States (US) is a community of organizations that collaborate in collecting and processing intelligence for the US. The IC relies on human-machine-based analytic strategies that 1) access and integrate vast amounts of information from disparate sources, 2) continuously process this information, so that, 3) a maximally comprehensive understanding of world actors and their behaviors can be developed and updated. Herein we describe an approach to utilizing outcomes-based learning (OBL) to support these efforts that is based on an ontology of the cognitive processes performed by intelligence analysts. Of particular importance to the Cognitive Process Ontology is the class Representation that is Warranted. Such a representation is descriptive in nature and deserving of trust in its veridicality. The latter is because a Representation that is Warranted is always produced by a process that was vetted (or successfully designed) to reliably produce veridical representations. As such, Representations that are Warranted are what in other contexts we might refer to as ‘items of knowledge’.
Keywords intelligence analysis  outcomes-based research  cognitive ontology  sabermetrics
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References found in this work BETA

Warrant and Proper Function.Alvin Plantinga - 1993 - Oxford University Press.

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Toward a General Theory of Knowledge.Luis M. Augusto - 2020 - Journal of Knowledge Structures and Systems 1 (1):63-97.

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