Situational Understanding in the Human and the Machine release_zeamg7i7rbc6rgh5ev7ffamx5a

by Yan Yufik, Raj Malhotra

Published in Frontiers in Systems Neuroscience by Frontiers Media SA.

2021   Volume 15, p786252

Abstract

The Air Force research programs envision developing AI technologies that will ensure battlespace dominance, by radical increases in the speed of battlespace understanding and decision-making. In the last half century, advances in AI have been concentrated in the area of machine learning. Recent experimental findings and insights in systems neuroscience, the biophysics of cognition, and other disciplines provide converging results that set the stage for technologies of machine understanding and machine-augmented Situational Understanding. This paper will review some of the key ideas and results in the literature, and outline new suggestions. We define situational understanding and the distinctions between understanding and awareness, consider examples of how understanding—or lack of it—manifest in performance, and review hypotheses concerning the underlying neuronal mechanisms. Suggestions for further R&D are motivated by these hypotheses and are centered on the notions of Active Inference and Virtual Associative Networks.
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https://www.frontiersin.org/articles/10.3389/fnsys.2021.786252/full
2022-02-04 12:11:05 | 42 resources
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Date   2021-12-23
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