Number Understanding Modelling in Behavioural Embodied Robotic Systems

数学能力可以赋予机器人必要的抽象和符号处理能力，这是提高其认知能力和与人类的社会互动所必需的。NUMBERS项目的目标是通过模仿人类学习数字的方法，建立一种新的人工数学认知模型，以发展机器人对数字的理解能力。这将为儿童数学能力发展的发展心理学和神经科学研究提供一种新的工具。Cangelosi教授说，这一目标将通过一个高度跨学科的研究计划来实现，该计划将利用相关领域的领先学者的合作。（认知发展机器人），普利茅斯大学，和教授麦克莱兰（计算心理学）、美国斯坦福大学，以及一家产业合作伙伴的技术支持NUMBERS的研究活动将利用谢菲尔德机器人公司提供的尖端设施，这是谢菲尔德大学和谢菲尔德哈勒姆大学的一项联合计划，该大学将主持该项目。事实上，该模型将与最先进的儿童机器人平台之一（“iCub”）集成，因此，通过逼真的实验进行验证，类似于儿童数学认知的科学实验。在交互式机器人实验的数值认知的新模型的验证将构成一个模块化的方法，以生物启发的人工智能架构所提供的增强功能的概念证明。此外，移动的设备的优化实现将被实现，以缩小空间和功率要求的计算，增加应用的机会。这一基础研究将提供方法论基础和认知合理的工程原则，为下一代的社会互动机器人，模仿人类智能的先进能力，真实的理解和与外部世界的互动。研究结果将有助于设计更有效的认知机器人系统，能够学习抽象的符号数字处理在一个更灵活和生态的方式。类人的学习和互动的特点，可以让人们更容易地识别所需的社会序曲，机器人正在进行，或促进转移的技能，在人与人的互动，人与机器人相遇。这种设想的人性化将积极影响机器人在社会环境中的接受程度，因为它们将被视为不那么危险，增加未来机器人的社会经济应用，这些机器人可以承担曾经被认为过于微妙或不经济的任务。这在社会关怀、陪伴、治疗、家庭援助、娱乐和教育领域尤其重要。

Mathematical competence can endow robots of the necessary capability for abstract and symbolic processing, which is required for improving their cognitive performance and their social interaction with human beings. But so far, only few attempts have been made to apply mathematical cognition in robots.The objective of the NUMBERS project is to construct a novel artificial cognitive model of mathematical cognition by imitating human like learning approaches for developing number understanding. This will provide a novel tool for developmental psychology and neuroscience research on the development of mathematical abilities in children. The objective will be achieved through a highly interdisciplinary research program that will take advantage of the collaboration of leading academics in the fields involved, prof. Cangelosi (Cognitive Developmental Robotics), Plymouth University, and prof. McClelland (Computational Psychology), Stanford University, USA, and the technical support of an industrial partner (NVIDIA Corporation, USA and UK).The NUMBERS' research activities will exploit the cutting-edge facilities offered by Sheffield Robotics, a joint initiative between the University of Sheffield and Sheffield Hallam University, which will host the project. Indeed, the model will be integrated with one of the most advanced child-like robotic platform (the "iCub") and, therefore, validated through realistic experiments, resembling scientific experiments of mathematical cognition in children. The validation of the novel model of the numerical cognition in interactive robotic experiments will constitute a proof of concept of the enhanced capabilities offered by a modular approach to bio-inspired artificial intelligence architectures. Furthermore, an optimised implementation for mobile devices will be realised in order to downsize space and power requirements for the computation, increasing application opportunities.This foundational research will provide the methodological basis and cognitively plausible engineering principles for the next generation of socially interactive robots, mimicking advanced capabilities of the human intelligence for real understanding and interaction with the external world. Results will help the design of more efficient cognitive robotic systems capable of learning abstract symbolic number processing in a more flexible and ecological manner.The human-like learning and interaction are characteristics that might allow people to more easily identify the desired social overture that the robot is making, or facilitate the transfer of skills learned in human-human interactions to human-robot encounters. This envisioned humanization will positively affect the acceptance of robots in social environments, as they will be perceived as less dangerous, increasing the socio-economic applications of future robots that can take on tasks once thought too delicate or uneconomical to automate. This is particularly relevant in the fields of social care, companionship, therapy, domestic assistance, entertainment, and education.