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Integrating case-based reasoning in multi-criteria decision support systems

Author: Dutta, Soumitra ; Angehrn, Albert A.INSEAD Area: Technology and Operations Management In: Uncertainty in artificial intelligence 6 - Bonissone, Piero P. - 1991 - Book Language: EnglishDescription: p. 133-150.Type of document: INSEAD ChapterNote: Please ask the Library for this chapter.Abstract: An important focus in current research on deision support systems (DSS) is the design of flexible environments to facilitate and support learning about the problem domain by the user. This research uses case-based reasoning to develop a symbiotic DSS in which both the user and the DSS learn from each other. The user learns from the DSS (from stored prior problem solution) and the system learns from the user (by observing current problem-solving behaviours). The specific context of our research is the class of DSS used for supporting multi-criteria decision making (MCDM). The projects includes the implementation of a prototype extension of the Triple C MCDSS
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An important focus in current research on deision support systems (DSS) is the design of flexible environments to facilitate and support learning about the problem domain by the user. This research uses case-based reasoning to develop a symbiotic DSS in which both the user and the DSS learn from each other. The user learns from the DSS (from stored prior problem solution) and the system learns from the user (by observing current problem-solving behaviours). The specific context of our research is the class of DSS used for supporting multi-criteria decision making (MCDM). The projects includes the implementation of a prototype extension of the Triple C MCDSS

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