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Summary: Knowledge-Intensive Case-Based Reasoning and
Intelligent Tutoring
Agnar Aamodt
Department of Computer and Information Science
Norwegian University of Science and Technology (NTNU)
NO-7491 Trondheim
Norway
agnar.aamodt@idi.ntnu.no
Abstract. Knowledge-intensive CBR assumes that cases are enriched with
general domain knowledge. In the system Creek, developed in our group, there
is a strong coupling between cases and general domain knowledge, in that cases
are embedded within a semantic network of domain concepts and relations.
Although mostly used for decision support, this architecture is also being
explored for the purpose of interactive learning support. The theme of the talk
is twofold: Integration of cases and general domain knowledge within the
knowledge-intensive CBR system Creek, and a discussion of different ways this
framework can be used to build intelligent computer-assisted learning systems.
1 Introduction
A knowledge-intensive case-based reasoning method assumes that cases, in some
way or another, are enriched with explicit general domain knowledge [1,2]. The role
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