Rasheed Nadia, Amin Shamsudin H M
Faculty of Electrical Engineering, Universiti Teknologi Malaysia, 81310 Skudai, Johor, Malaysia; University College of Engineering and Technology, The Islamia University of Bahawalpur, Bahawalpur 63100, Pakistan.
Faculty of Electrical Engineering, Universiti Teknologi Malaysia, 81310 Skudai, Johor, Malaysia; Centre for Artificial Intelligence & Robotics (CAIRO), Universiti Teknologi Malaysia, 54100 Kuala Lumpur, Malaysia.
Comput Intell Neurosci. 2016;2016:8571265. doi: 10.1155/2016/8571265. Epub 2016 Mar 16.
Grounded language acquisition is an important issue, particularly to facilitate human-robot interactions in an intelligent and effective way. The evolutionary and developmental language acquisition are two innovative and important methodologies for the grounding of language in cognitive agents or robots, the aim of which is to address current limitations in robot design. This paper concentrates on these two main modelling methods with the grounding principle for the acquisition of linguistic ability in cognitive agents or robots. This review not only presents a survey of the methodologies and relevant computational cognitive agents or robotic models, but also highlights the advantages and progress of these approaches for the language grounding issue.
基于情境的语言习得是一个重要问题,特别是对于以智能且有效的方式促进人机交互而言。进化和发展语言习得是在认知主体或机器人中实现语言情境化的两种创新且重要的方法,其目的是解决当前机器人设计中的局限性。本文专注于这两种主要的建模方法以及在认知主体或机器人中获取语言能力的情境化原则。这篇综述不仅对这些方法以及相关的计算认知主体或机器人模型进行了概述,还突出了这些方法在语言情境化问题上的优势和进展。