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19 May 2011 Categorification of the layered sensing construct
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We propose a mathematical formulation for a layered sensing architecture based on the theory of categories that will allow us to abstractly define agents and their interactions in such a way that we can treat human and machine (or systems of these) agents homogeneously. One particular advantage is that this general formulation will allow the development of multi-resolution analyses of a given situation that is independent of the particular models used to represent a given agent or system of agents. In this paper, we define the model and prove basic facts that will be fundamental in future work. Central to our approach is the integration of uncertainty into our model. Such a framework is necessitated by our desire to define (among other things) measures of alignment and efficacy for systems of heterogeneous agents operating in a diverse and complex environment.
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Kirk Sturtz, Jared Culbertson, Mark E. Oxley, and Steven K. Rogers "Categorification of the layered sensing construct", Proc. SPIE 8059, Evolutionary and Bio-Inspired Computation: Theory and Applications V, 80590D (19 May 2011);

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