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

机译:将思想自适应理论转移到社会机器人:从发育心理到机器人的见解

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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:尽管近期社会机器人领域的进步,但重要的局限性抑制了其进度和延迟了机器人在日常情况下的应用。在本文中,我们建议开发通过我们对人类婴儿社会适应能力的知识启发的计算模型。我们认为这可以在建筑层面提供解决方案以克服当前系统的限制。具体而言,我们展示了适应性心理(TOM)系统将支持机器人学(即,男人算作信仰理解,接受性和准备,积极感知和学习)的功能优势,并在实际应用中对其进行体现。我们审查了当前的计算模型,主要基于仿真和上行理论,以及机器人实现,以确定汤姆功能在当前机器人体系结构中的局限性,并提出了可能的未来发展途径。最后,我们提出了未来的研究,创造了集成模拟和目的方法的性质,以提高机器人的适应性汤姆能力的创新计算模型,以提高人机互动,允许在未探测的环境中应用机器人,例如灾难和建筑工地。为实现这一目标,我们建议将未来的研究指导对机器人和发育心理学领域的调制解调器串扰。

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