A Methodology for Modeling and Representing Expert Knowledge That Supports Teaching-Based Intelligent Agent Development
Abstract
The long term research goal of our research group is to change the way a knowledge-based agent is built, from being programmed by a knowledge engineer (based on what he or she has learned from a domain expert) to being directly taught by a domain expert that receives limited or no support from a knowledge engineer. The investigated approach, called Disciple (Tecuci, 1998), relies on developing a very capable learning and reasoning agent that can collaborate with a domain expert to develop its knowledge base consisting of an ontology that defines the terms from the application domain, and a set of general task reduction rules expressed with these terms. An important component of this research is the development of a general methodology for modeling and representing expert knowledge that supports teaching-
Cite
Text
Bowman et al. "A Methodology for Modeling and Representing Expert Knowledge That Supports Teaching-Based Intelligent Agent Development." AAAI Conference on Artificial Intelligence, 2000.Markdown
[Bowman et al. "A Methodology for Modeling and Representing Expert Knowledge That Supports Teaching-Based Intelligent Agent Development." AAAI Conference on Artificial Intelligence, 2000.](https://mlanthology.org/aaai/2000/bowman2000aaai-methodology/)BibTeX
@inproceedings{bowman2000aaai-methodology,
title = {{A Methodology for Modeling and Representing Expert Knowledge That Supports Teaching-Based Intelligent Agent Development}},
author = {Bowman, Michael and Tecuci, Gheorghe and Boicu, Mihai},
booktitle = {AAAI Conference on Artificial Intelligence},
year = {2000},
pages = {1065},
url = {https://mlanthology.org/aaai/2000/bowman2000aaai-methodology/}
}