Knowledge Engineering in the Long Game of Artificial Intelligence: The Case of Speech Acts
Artificial Intelligence
2022-02-03 v1
Abstract
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.
Keywords
Cite
@article{arxiv.2202.01040,
title = {Knowledge Engineering in the Long Game of Artificial Intelligence: The Case of Speech Acts},
author = {Marjorie McShane and Jesse English and Sergei Nirenburg},
journal= {arXiv preprint arXiv:2202.01040},
year = {2022}
}
Comments
Presented at The Ninth Advances in Cognitive Systems (ACS) Conference 2021 (arXiv:2201.06134)