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Knowledge Engineering in the Long Game of Artificial Intelligence: The Case of Speech Acts

arXiv 2202.01040 ↗First posted 2 Feb 2022cs.AIcited by 1

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Abstract (arXiv)

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.

Key facts. Cited by 1 paper in the map (data through 7 Oct 2026). Builds on 1 of its 24 references that are in the map. First posted on arXiv 2 Feb 2022.

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  1. 2018Deep Learning: A Critical Appraisalcited by 214

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