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Proceedings Paper

VoI for complex AI based solutions in coalition environments
Author(s): Dinesh Verma; Geeth de Mel; Gavin Pearson
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Paper Abstract

Real-life AI based solutions usually consist of a complex chain of processing elements, which may include a mixture of machine learning based approaches and traditional programmed knowledge. The solution uses this chain of processing elements to convert input information into an output decision. When information is provided for a specific solution, the impact of the information on the decision can be measured quantitatively as a Value of Information (VoI) metric. In prior work, we have considered how the VoI metric can be defined for a single AI-based processing element. To be useful in real-life solution instances, the VoI metric needs to be enhanced to handle a complex chain of processors, and be extended to AI-based solutions, as well as supporting elements that may not necessarily use AI. In this paper, we propose a definition of VoI that can be used across AIbased processing, as well as non AI based processing, and show how the construct can be used to analyze and understand the impact of a piece of information on a chain of processing elements.

Paper Details

Date Published: 10 May 2019
PDF: 7 pages
Proc. SPIE 11006, Artificial Intelligence and Machine Learning for Multi-Domain Operations Applications, 1100609 (10 May 2019); doi: 10.1117/12.2519619
Show Author Affiliations
Dinesh Verma, IBM Thomas J. Watson Research Ctr. (United States)
Geeth de Mel, IBM United Kingdom Ltd. (United Kingdom)
Gavin Pearson, United Kingdom Ministry of Defence (United Kingdom)

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

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