Knowledge Engineering in the Long Game of Artificial Intelligence: The Case of Speech Acts
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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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References · 1
- 2018Deep Learning: A Critical Appraisalcited by 214
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- 2022The Path to Autonomous Learnerscited by 0
- 2022The Path to Autonomous Learners4 Nov 2022