eTALK embodied Thought for Abstract Language Knowledge

语言是人与人之间最自然的交流方式，也是人与机器人之间最自然的互动方式。由于人们使用的绝大多数单词都是抽象单词，为了实现与机器人的自然语言交互，机器能够处理具体和抽象概念至关重要。这个及时的项目战略性地建立在发展心理学和抽象概念的认知理论，发展机器人和认知建模的人工智能方法，以及人机交互和语言使用的最新实质性进展之上，以引导我们对机器人代理中抽象概念和词语的科学和技术理解。该项目将开发和测试一种新的认知发展架构，利用最新的生成式深度学习模型和发展机器人方法进行人机交互实验，通过环绕迁移学习具体和抽象单词。三个案例研究已战略性地计划，以显示所提出的方法的广度和鲁棒性，并展示了灵活的计算方法，在处理各种类型的抽象概念。案例研究的重点是：（i）抽象的词基础的知觉，运动和情感的概念，（ii）数字词的学习，和（iii）功能词的指示（指示）介词，关于时间和模糊量词的话。该项目将导致我们对语言和认知的基础和体现基础的计算方法的更深入理解的突破，以及人形机器人的设计，这些机器人可以学习理解并采取行动，关于各种抽象单词的对话，因为这些都是内在地基于他们自己的感觉运动经验。该项目将受益于与应用领域的用户和利益相关者的直接参与，以及来自学术界和工业界的国际顾问。

Language is the most natural means of communication among people, as well as for interaction betweenpeople and robots. As the great majority of words people use are abstract words, to achieve natural languageinteraction with robots it is crucial that machines can handle both concrete and abstract concepts. This timelyproject strategically builds on the recent, substantial advances in developmental psychology and embodiedcognition theories on abstract concepts, on developmental robotics and AI methods for cognitive modelling,and in human-robot interaction and language use, to bootstrap our scientific and technological understandingof the grounding of abstract concepts and words in robotic agents. The project will develop and test a novelcognitive developmental architecture utilising the latest generative deep learning models and developmentalrobotics methods for human-robot interaction experiments on the learning of concrete and abstract words viagrounding transfer. Three case studies have been strategically planned to show the breadth and robustness ofthe proposed approach, and to demonstrate the flexibility of the computational approach in dealing withvarious types of abstract concepts. The case studies focus on: (i) abstract word grounding for perceptual,motor and affective concepts, (ii) number word learning, and (iii) function words for demonstrative (deictic)prepositions, words about time and fuzzy quantifiers. This project will lead to breakthroughs in our deeperunderstanding of the computational approaches to the grounding and embodiment bases of language andcognition and in the design of humanoid robots which can learn to understand, and act on, conversationsabout a variety of abstract words, as these are intrinsically grounded in their own sensorimotor experience.The project will benefit from direct engagement with users and stakeholders of the application domains, aswell as from the international advisors from both academia and industry.