Author:
Cecilia Zanni-Merk
Affiliation:
INSA de Strasbourg, France
Keyword(s):
Knowledge Technologies, Ontologies, Reasoning, Experience, Meta-knowledge.
Related
Ontology
Subjects/Areas/Topics:
Applications and Case-studies
;
Artificial Intelligence
;
Business Analytics
;
Cardiovascular Technologies
;
Computing and Telecommunications in Cardiology
;
Data Engineering
;
Decision Support Systems
;
Decision Support Systems, Remote Data Analysis
;
Health Engineering and Technology Applications
;
Knowledge Engineering and Ontology Development
;
Knowledge Representation
;
Knowledge-Based Systems
;
Symbolic Systems
Abstract:
This article presents a generic knowledge-based framework for problem solving in Engineering, in a broad
sense. After a discussion about the drawbacks of the traditional architecture used for deploying knowledge-based
systems (KBS), the KREM (Knowledge, Rules, Experience, Meta-Knowledge) architecture is presented.
The novelty of the proposal comes from the inclusion of experience capitalization and of meta-knowledge use
into the previously discussed traditional architecture. KREM improves the efficiency of classic KBSs, as it
permits to deal with incomplete expert knowledge models, by progressively completing them, learning with
experience. Also, the use of meta-knowledge can steer their execution more efficiently. This framework has
been successfully used in different projects. Here, the architecture of the KREM model is presented along
with some implementation issues and three case studies are discussed.