不确定性下以士兵为中心的人-智能体决策的融合推理

A. Raglin, Andre V Harrison, Douglas Summers-Stay
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引用次数: 5

摘要

随着智能体(设备和软件)越来越多地融入我们生活的方方面面,人类智能体团队的研究领域受到了越来越多的关注。考虑到士兵们目前和将来面临的多样化、动态和快节奏的作战,这一点尤其正确。人们普遍认为,在未来,机器的速度将远远超过士兵的反应能力,甚至超过他们理解数字队友复杂活动的能力,这是一个令人担忧的问题。在这种加速的环境中,不确定性将带来独特的、不可预见的挑战,可能会抑制士兵有效决策的能力,并有效地做出足够快的决策,以支持未来战场的节奏。为了加快陆军行动中的决策制定,军方正在依赖代理和使能技术,如集成智能传感器网络和自主设备的复杂系统。这些系统的系统将由支持机器学习的人工智能算法驱动,并将与人类作战人员组成团队,双方必须作为一个整体来完成任务。解释可以为人类提供有关复杂系统的数据或行为的关键信息,以帮助人类代理团队。
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FUSED REASONING UNDER UNCERTAINTY FOR SOLDIER CENTRIC HUMAN-AGENT DECISION MAKING
As agents (devices and software) are increasingly incorporated into every aspect of our lives, the research area of human-agent teaming has seen an increase in attention. This is particularly true considering the varied, dynamic, and fast pace operations Soldiers are currently facing and will be facing in the future. There is a common idea that, in the future, the speed of machines will far exceed a Soldiers’ ability to react or even comprehend the complex activities of their digital teammates, which is a concern. Uncertainty in this accelerated environment will present unique and unforeseen challenges that may potentially inhibit a Soldier’s ability to make decisions effectively and to efficiently decide fast enough to support the future battlefield optempo. To accelerate decision making in Army operations the military is relying on agents and enabling technologies such as complex systems that integrate intelligent sensor networks and autonomous devices. These systems-of- systems will be driven by machine learning enabled artificial intelligence algorithms and will form teams with human warfighters, where both must act as one unit to accomplish their mission. Explanations can provide key information about the data or behavior of complex systems to the human to aide human agent teaming.
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