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Transferring Adaptive Theory of Mind to Social Robots: Insights from Developmental Psychology to Robotics

机译:将适应性思维理论转移到社交机器人:从发展心理学到机器人的见解

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Despite the recent advancement in the social robotic field, important limitations restrain its progress and delay the application of robots in everyday scenarios. In the present paper, we propose to develop computational models inspired by our knowledge of human infants' social adaptive abilities. We believe this may provide solutions at an architectural level to overcome the limits of current systems. Specifically, we present the functional advantages that adaptive Theory of Mind (ToM) systems would support in robotics (i.e., men-talizing for belief understanding, proactivity and preparation, active perception and learning) and contextualize them in practical applications. We review current computational models mainly based on the simulation and teleological theories, and robotic implementations to identify the limitations of ToM functions in current robotic architectures and suggest a possible future developmental pathway. Finally, we propose future studies to create innovative computational models integrating the properties of the simulation and teleological approaches for an improved adaptive ToM ability in robots with the aim of enhancing human-robot interactions and permitting the application of robots in unexplored environments, such as disasters and construction sites. To achieve this goal, we suggest directing future research towards the modem cross-talk between the fields of robotics and developmental psychology.
机译:尽管社交机器人领域最近有了进步,但重要的限制限制了它的发展,并延迟了机器人在日常场景中的应用。在本文中,我们建议开发受人类婴儿社会适应能力知识启发的计算模型。我们认为,这可以在体系结构级别上提供解决方案,以克服当前系统的限制。具体而言,我们展示了自适应心智理论(ToM)系统将在机器人技术中支持的功能优势(即诱人的信念理解,主动性和准备性,主动知觉和学习),并在实际应用中将其上下文化。我们主要基于仿真和目的论理论以及机器人实现对当前的计算模型进行回顾,以识别ToM功能在当前机器人体系结构中的局限性,并提出可能的未来发展道路。最后,我们提出了未来的研究,以创建创新的计算模型,以融合仿真和目的论方法的特性,从而提高机器人的自适应ToM能力,以增强人机交互性并允许机器人在未开发的环境(例如灾难)中应用和建筑工地。为了实现这一目标,我们建议将未来的研究引向机器人技术与发展心理学领域之间的现代串扰。

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