Qualitative reasoning can generate ambiguous behaviors due to the lack of quantitative information. Despite many different research results focusing on ambiguities reduction, fundamentally it is impossible to totally remove ambiguities with only qualitative methods and to guarantee the consistency of results. This prevents the wide use of qualitative reasoning techniques in practical situations, particularly in conceptual design, where qualitative reasoning is considered intrinsically useful. To improve this situation, this paper initially investigates the origin of ambiguities in qualitative reasoning. Then it proposes a method based on intelligent interventions of the user who is able to detect ambiguities, to prioritize interventions on these ambiguities, and to reduce ambiguities based on the least commitment strategy. This interaction method breaks through the limit of qualitative reasoning in practical applications to conceptual design. The method was implemented as a new feature in a software tool called the Knowledge Intensive Engineering Framework in order to be tested and used for a printer design.
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