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Situational Understanding in the Human and the Machine.
- Source :
- Frontiers in Systems Neuroscience; 12/23/2021, Vol. 15, p1-24, 24p
- Publication Year :
- 2021
-
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. [ABSTRACT FROM AUTHOR]
- Subjects :
- VIRTUAL networks
MACHINE learning
ARTIFICIAL intelligence
BIOPHYSICS
AIR forces
Subjects
Details
- Language :
- English
- ISSN :
- 16625137
- Volume :
- 15
- Database :
- Complementary Index
- Journal :
- Frontiers in Systems Neuroscience
- Publication Type :
- Academic Journal
- Accession number :
- 154328285
- Full Text :
- https://doi.org/10.3389/fnsys.2021.786252