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通过人与动物协作模型理解人机协作团队

Understanding Human-Autonomy Teams Through a Human-Animal Teaming Model.

机构信息

Human Systems Engineering, Fulton School of Engineering, Arizona State University.

Human Factors and Applied Cognition Group, Department of Psychology, George Mason University.

出版信息

Top Cogn Sci. 2024 Jul;16(3):554-567. doi: 10.1111/tops.12713. Epub 2023 Nov 27.

Abstract

The relationship between humans and animals is complex and influenced by multiple variables. Humans display a remarkably flexible and rich array of social competencies, demonstrating the ability to interpret, predict, and react appropriately to the behavior of others, as well as to engage others in a variety of complex social interactions. Developing computational systems that have similar social abilities is a critical step in designing robots, animated characters, and other computer agents that appear intelligent and capable in their interactions with humans and each other. Further, it will improve their ability to cooperate with people as capable partners, learn from natural instruction, and provide intuitive and engaging interactions for human partners. Thus, human-animal team analogs can be one means through which to foster veridical mental models of robots that provide a more accurate representation of their near-future capabilities. Some digital twins of human-animal teams currently exist but are often incomplete. Therefore, this article focuses on issues within and surrounding the current models of human-animal teams, previous research surrounding this connection, and the challenges when using such an analogy for human-autonomy teams.

摘要

人类与动物的关系是复杂的,受到多种变量的影响。人类表现出了非常灵活和丰富的社交能力,能够解释、预测和适当地对他人的行为做出反应,并与他人进行各种复杂的社交互动。开发具有类似社交能力的计算系统是设计机器人、动画角色和其他计算机代理的关键步骤,这些代理在与人类和彼此交互时表现出智能和能力。此外,这将提高它们作为有能力的合作伙伴与人类合作、从自然指导中学习以及为人类合作伙伴提供直观和吸引人的交互的能力。因此,人类-动物团队模拟可以是促进机器人真实心理模型的一种手段,这种模型更准确地代表了它们的近期能力。一些人类-动物团队的数字双胞胎目前已经存在,但往往不完整。因此,本文重点讨论当前人类-动物团队模型内部和周围的问题、围绕这一联系的先前研究,以及在使用这种类比进行人类自主团队时的挑战。

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