Authors:
Sergei Nirenburg
1
;
Marjorie McShane
1
;
Stephen Beale
1
and
Roberta Catizone
2
Affiliations:
1
University of Maryland Baltimore County, United States
;
2
Onyx Consulting, United Kingdom
Keyword(s):
Knowledge engineering, Knowledge elicitation, Ontology, Intelligent agents, Automatic reasoning, Influence diagrams.
Related
Ontology
Subjects/Areas/Topics:
Agents
;
Artificial Intelligence
;
Artificial Intelligence and Decision Support Systems
;
Biomedical Engineering
;
Decision Support Systems
;
Distributed and Mobile Software Systems
;
Enterprise Information Systems
;
Expert Systems
;
Health Information Systems
;
Knowledge Acquisition
;
Knowledge Engineering and Ontology Development
;
Knowledge Representation
;
Knowledge-Based Systems
;
Multi-Agent Systems
;
Software Engineering
;
Symbolic Systems
Abstract:
This paper presents a case study showing how hybrid methods of knowledge elicitation can be used to build models in support of the functioning of intelligent agents. What facilitates both the elicitation of knowledge and its conversion into actionable models is the use of a unified representational knowledge scheme – spe-cifically, an unambiguous, ontologically grounded metalanguage that serves as the language of all recorded knowledge as well as the language in which agents remember and reason.