VoI for complex AI based solutions in coalition environments

Dinesh Verma; Geeth de Mel; Gavin Pearson

doi:10.1117/12.2519619

10 May 2019 VoI for complex AI based solutions in coalition environments

Dinesh Verma, Geeth de Mel, Gavin Pearson

Proceedings Volume 11006, Artificial Intelligence and Machine Learning for Multi-Domain Operations Applications; 1100609 (2019) https://doi.org/10.1117/12.2519619
Event: SPIE Defense + Commercial Sensing, 2019, Baltimore, MD, United States

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.

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Citation Download Citation

Dinesh Verma, Geeth de Mel, and Gavin Pearson "VoI for complex AI based solutions in coalition environments", Proc. SPIE 11006, Artificial Intelligence and Machine Learning for Multi-Domain Operations Applications, 1100609 (10 May 2019); https://doi.org/10.1117/12.2519619

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