RI: Small: Collaborative Reference in Open Domains

RI：小型：开放域中的协作参考

• 批准号: 1017811
• 负责人: Matthew Stone
• 金额: $ 10万
• 依托单位: Rutgers University New Brunswick
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2010
• 资助国家: 美国
• 起止时间: 2010-08-15 至 2012-07-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1017811&HistoricalAwards=false
• 关键词: RI; Small; Collaborative; Reference; Open

Reference, the ability to single out objects in the world usinglinguistic expressions, is a fundamental part of communication.Cognitive scientists have showed that people collaborate on reference,for example by negotiating about how to describe things. This projectlays the groundwork for computer systems that can do the same.Eventual applications range from talking robots that can communicatewith people in real physical environments, to tutoring anddecision-support systems that can give comprehensible explanations ofspecialized concepts. These applications are open domains, in thesense that one interlocutor, or both, may have no simple descriptorfor an unfamiliar object. So the system has to have flexiblestrategies for describing things in words and inference mechanismsthat acknowledge the possibility of a misunderstanding by eithersystem or user.This project undertakes exploratory work on the communicativestrategies and inference mechanisms required for collaborativereference in open domains. During the academic year, PI Stone workswith a computer science student to extend a prototype system withadditional methods for collaborating under uncertainty, drawing on thestudent's ongoing research in cognitive modeling, planning andlearning. During the summer, Stone works with a three-memberinterdisciplinary team doing corpus analysis, grammar development andintegration to characterize generic strategies for describing shape,using rough descriptions and part-whole relationships. The resultsare an open-source prototype with more general collaborative referenceabilities along with specific hypotheses, informed by publishablelinguistic and conceptual analyses, about how these abilities mightaffect the system's success in referring to unfamiliar objects.

指称是指使用语言表达来挑选世界上的事物的能力，是交流的基本部分。认知科学家已经证明，人们在指称上进行合作，例如通过协商如何描述事物。这一项目为可以做同样事情的计算机系统奠定了基础。从可以在真实物理环境中与人交流的会说话的机器人，到可以对专门概念进行可理解解释的教学和决策支持系统，这些应用程序的范围很广。这些应用程序是开放的领域，从某种意义上说，一个或两个对话者可能没有简单的描述符来描述一个不熟悉的对象。因此，系统必须有灵活的文字描述策略和推理机制，以承认系统或用户可能会产生误解。本项目对开放领域中协作参照所需的交流策略和推理机制进行了探索性工作。在本学年，Pi Stone与一名计算机科学专业的学生合作，利用学生在认知建模、规划和学习方面的持续研究，用其他方法扩展了一个原型系统，用于在不确定情况下进行协作。今年夏天，斯通与一个由三名成员组成的跨学科团队合作，进行语料库分析、语法开发和整合，以表征描述形状的一般策略，使用粗略描述和部分-整体关系。结果是一个开放源码原型，具有更广泛的协作参考能力，以及特定的假设，通过出版的语言学和概念分析，这些能力可能如何影响系统在引用陌生对象时的成功。