This paper describes principles and practices of knowledge engineering that enable the development of holistic language-endowed intelligent agents that can function across domains and applications, as well as expand their ontological and lexical knowledge through lifelong learning. For illustration, we focus on dialog act modeling, a task that has been widely pursued in linguistics, cognitive modeling, and statistical natural language processing. We describe an integrative approach grounded in the OntoAgent knowledge-centric cognitive architecture and highlight the limitations of past approaches that isolate dialog from other agent functionalities.
翻译:本文件介绍了知识工程的原则和做法,这些知识工程有助于开发能够跨领域和跨应用运作的整体语言内涵智能剂,并通过终身学习扩大其本体学和词汇学知识。例如,我们侧重于对话行为模型,这是语言学、认知模型和统计自然语言处理中广泛追求的一项任务。我们描述了基于OntoAgenti知识中心认知架构的综合方法,并突出强调了以往将对话与其他代理功能隔离开来的做法的局限性。