Grounding Language for Interactive Task Learning
Grounding Language for Interactive Task Learning
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交互式任务学习的基础语言
作者：
Peter Lindes;Aaron Mininger;James R. Kirk;J. Laird
本文描述了语言如何通过名为Rosie的机器人代理中名为Lucia的理解系统来建立，该机器人代理可以操纵物体并在室内导航。整个系统建立在Soar认知架构内，并使用嵌入式构造语法（ECG）作为描述语言知识的形式主义。接地是使用来自语法本身的知识，从语言环境，从代理感知，并从本体论的对象类别和属性和动作的代理可以执行的长期知识。本文还描述了一个基准语料库的200句话在这个领域随着测试版本的世界模型和本体和黄金标准的意义，每个句子沿着。基准包含在补充材料中。
This paper describes how language is grounded by a comprehension system called Lucia within a robotic agent called Rosie that can manipulate objects and navigate indoors. The whole system is built within the Soar cognitive architecture and uses Embodied Construction Grammar (ECG) as a formalism for describing linguistic knowledge. Grounding is performed using knowledge from the grammar itself, from the linguistic context, from the agents perception, and from an ontology of long-term knowledge about object categories and properties and actions the agent can perform. The paper also describes a benchmark corpus of 200 sentences in this domain along with test versions of the world model and ontology and gold-standard meanings for each of the sentences. The benchmark is contained in the supplemental materials.