Situational Understanding in the Human and the Machine

Author:

Yufik Yan,Malhotra Raj

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.

Publisher

Frontiers Media SA

Subject

Cellular and Molecular Neuroscience,Cognitive Neuroscience,Developmental Neuroscience,Neuroscience (miscellaneous)

Cited by 1 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Situation-Based Neuromorphic Memory in Spiking Neuron-Astrocyte Network;IEEE Transactions on Neural Networks and Learning Systems;2023

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