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Proceedings Paper

Contingent attention management in multitasked environments
Author(s): Hesham Fouad; Ranjeev Mittu; Derek Brock
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Paper Abstract

Artificial Intelligence (AI) technology is being applied successfully in a number of domains. Advances in low cost, high performance computing platforms have made AI approaches sufficiently scalable to be applied in high volume, commercial applications. The true promise of AI in modeling human intelligence remains elusive. Current approaches can simulate a small subset of the many processes that make up human cognition, and yet it would be of huge benefit to be able to integrate expert human decision making in AI applications. In this paper, we present a pragmatic approach that can be used to capture expert human decision making within a limited domain of expertise. We propose an approach that automates the Analytic Hierarchy Process in order to capture a model of expert decision making from observational data. While this is not a general solution, it provides a workable approach for AI applications dealing with well defined, limited domains of knowledge.

Paper Details

Date Published: 10 May 2019
PDF: 6 pages
Proc. SPIE 11006, Artificial Intelligence and Machine Learning for Multi-Domain Operations Applications, 1100620 (10 May 2019); doi: 10.1117/12.2524979
Show Author Affiliations
Hesham Fouad, U.S. Naval Research Lab. (United States)
Ranjeev Mittu, U.S. Naval Research Lab. (United States)
Derek Brock, U.S. Naval Research Lab. (United States)

Published in SPIE Proceedings Vol. 11006:
Artificial Intelligence and Machine Learning for Multi-Domain Operations Applications
Tien Pham, Editor(s)

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