信息融合探索

Erik Blasch, S. Rogers, Jared Culbertson, A. Rodríguez, L. Fenstermacher, R. Patterson
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引用次数: 6

摘要

基于质量的感知技术开发(QuEST)是一种创建认知外骨骼以提高人机决策质量的方法。本文从人机信息融合的角度出发,讨论了QuEST的动机。基于操作者的情境感知包括外部感官知觉和内部认知解释两个要素。我们概述了实现人类智能放大(IA)的推理方法的QuEST元素和原则,而不是来自机器人工智能(AI)的数据聚合。在自动目标开发的用例示例中,我们展示了需要增强对人(身心认知)和机器(基于传感器的推理)的理解,以建立情景活动的内聚叙述。
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QuEST for information fusion
Qualia-based Exploitation of Sensing Technology (QuEST) is an approach to create a cognitive exoskeleton to improve human-machine decision quality. In this paper, we discuss the motivation of QuEST as it pertains to man-machine information fusion. Operator-based situation awareness includes both elements of external sensory perception and internal cognitive explanation. We outline QuEST elements and tenets towards a reasoning approach that achieves human intelligence amplification (IA) as opposed to data aggregation from machine artificial intelligence (AI). In a use case example for automatic target exploitation, we showcase the need for enhanced understanding of the man (mind-body cognition) and the machine (sensor-based reasoning) for establishing a cohesive narrative of situational activities.
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