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Enabling robotic social intelligence by engineering human social-cognitive mechanisms

机译:通过设计人类的社会认知机制来实现机器人社会智能

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For effective human-robot interaction, we argue that robots must gain social-cognitive mechanisms that allow them to function naturally and intuitively during social interactions with humans. However, a lack of consensus on social cognitive processes poses a challenge for how to design such mechanisms for artificial cognitive systems. We discuss a recent integrative perspective of social cognition to provide a systematic theoretical underpinning for computational instantiations of these mechanisms. We highlight several commitments of our approach that we refer to as Engineering Human Social Cognition. We then provide a series of recommendations to facilitate the development of the perceptual, motor, and cognitive architecture for this proposed artificial cognitive system in future work. For each recommendation, we highlight their relation to the discussed social-cognitive mechanisms, provide the rationale for these recommendations and potential benefits, and detail examples of associated computational formalisms that could be leveraged to instantiate our recommendations. Overall, the goal of this paper is to outline an interdisciplinary and multi-theoretic approach to facilitate the design of robots that will one day function, and be perceived, as socially interactive and effective teammates. (C) 2016 Published by Elsevier B.V.
机译:为了有效地进行人机交互,我们认为机器人必须获得社交认知机制,以使其在与人的社交互动中自然而直观地发挥作用。然而,在社会认知过程上缺乏共识对如何为人工认知系统设计这种机制提出了挑战。我们讨论了社会认知的最新综合观点,为这些机制的计算实例化提供了系统的理论基础。我们重点介绍了我们的方法的一些承诺,这些承诺被我们称为“工程人类社会认知”。然后,我们提供了一系列建议,以促进此拟议的人工认知系统在未来的工作中发展感知,运动和认知体系。对于每个建议,我们都突出显示了它们与所讨论的社会认知机制的关系,提供了这些建议的原理和潜在的好处,并详细介绍了可用于实例化我们的建议的相关计算形式主义的示例。总体而言,本文的目标是概述一种跨学科和多理论的方法,以促进机器人的设计,该机器人有一天会发挥作用,并被视为社交互动和有效的队友。 (C)2016由Elsevier B.V.发布

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