论文标题
对话是作为终身学习的工具
Dialog as a Vehicle for Lifelong Learning
论文作者
论文摘要
对话系统研究主要集中在两种主要应用程序类型围绕以任务为导向的对话系统，这些对话系统学会使用澄清来帮助理解目标和开放式的对话框系统，这些对话系统有望进行不受限制的“闲聊聊天”对话。但是，对话框交互也可以用于获得各种类型的知识，这些知识可用于改善基础语言理解系统或对话框进行的其他机器学习系统。在该职位论文中，我们提出了设计对话系统的问题，该问题使终身学习是一个重要的挑战问题，特别是对于涉及物理位置机器人的应用程序。我们包括朝这个方向上的先前工作的例子，并讨论尚待解决的挑战。
Dialog systems research has primarily been focused around two main types of applications - task-oriented dialog systems that learn to use clarification to aid in understanding a goal, and open-ended dialog systems that are expected to carry out unconstrained "chit chat" conversations. However, dialog interactions can also be used to obtain various types of knowledge that can be used to improve an underlying language understanding system, or other machine learning systems that the dialog acts over. In this position paper, we present the problem of designing dialog systems that enable lifelong learning as an important challenge problem, in particular for applications involving physically situated robots. We include examples of prior work in this direction, and discuss challenges that remain to be addressed.
