eTALK embodied Thought for Abstract Language Knowledge

eTALK体现了抽象语言知识的思想

• 批准号: EP/Y029534/1
• 负责人: Angelo Cangelosi
• 金额: $ 269.46万
• 依托单位: University of Manchester
• 依托单位国家: 英国
• 项目类别: Research Grant
• 财政年份: 2024
• 资助国家: 英国
• 起止时间: 2024 至 无数据
• 项目状态: 未结题
• 来源: https://gtr.ukri.org/projects?ref=EP%2FY029534%2F1
• 关键词: eTALK; embodied; Thought; Abstract; Language

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.

语言是人与人之间以及人与机器人之间最自然的交流方式。由于人们使用的绝大多数单词都是抽象单词，因此要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具身认知理论在抽象概念、发展机器人学和人工智能认知建模方法以及人机交互和语言使用方面的最新实质性进展的基础上，以引导我们对人类行为基础的科学和技术理解。机器人代理中的抽象概念和单词。该项目将开发和测试一种新颖的认知发展架构，利用最新的生成深度学习模型和开发机器人方法，进行人机交互实验，通过基础迁移学习具体和抽象单词。我们战略性地计划了三个案例研究，以展示所提出方法的广度和稳健性，并证明计算方法在处理各种类型的抽象概念时的灵活性。案例研究的重点是：（i）知觉、运动和情感概念的抽象词基础，（ii）数字词学习，以及（iii）指示（指示）介词的虚词，关于时间和模糊量词的词。该项目将在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方面取得突破，并在人形机器人的设计方面取得突破，这些机器人可以学习理解各种抽象单词的对话并采取行动，因为这些本质上是以他们自己的感觉运动经验为基础。该项目将受益于与应用领域的用户和利益相关者以及来自学术界和工业界的国际顾问的直接参与。