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IJCAI-99, Workshop ML-5: Automating the Construction of Case-Based Reasoners. Stockholm 1999. S. S. Anand, A. Aamodt, D.W. Aha (eds.). pp. 39-43. When using knowledge-intensive case-based
 

Summary: IJCAI-99, Workshop ML-5: Automating the Construction of Case-Based Reasoners. Stockholm 1999. S. S. Anand, A. Aamodt, D.W. Aha (eds.). pp. 39-43.
Abstract
When using knowledge-intensive case-based
reasoners, a key issue is to keep the know-
ledge-base updated. This is usually done by
having the user update the knowledge during the
retain phase, but machine-learning methods can
also be used. In this paper we discuss how an
elaboration phase, in which plausible inference
rules are derived, can be done in a goal-driven
manner to increase the systems automatic
learning capability.
1 Introduction
When faced with a new problem case, some case-based
reasoners use a knowledge base containing a model of
the domain in question. This knowledge base is used to
measure the similarity between the problem case and the
cases already solved and stored by the system. Although
this approach, known as knowledge-intensive case-based
reasoning, has shown promise in open and weak do-

  

Source: Aamodt, Agnar - Department of Computer and Information Science, Norwegian University of Science and Technology

 

Collections: Computer Technologies and Information Sciences