Combining Weighted Description Logic with Fuzzy Logic for Decision Making

In this paper we present a consensus-theoretic framework based on weighted description logic and on a consensus modelling approach, which is used to retrieve a consistent decision among experts along multi-attributes. We will show that the integration of these two approaches is best suited for consensus building between (human) experts, especially when their preferences are not easily found or disturbed by coincidental influences. As an application of our methodology, we interviewed experts (in our case students) on the choice of means of transport. One time we asked them directly about their preferences and another time we asked them about their attitudes towards ecology, economy, and others. We will show how these two approaches of gathering data lead to different constructed hypothetical consensus and how the additional use of weighted description logic reveals other diverse insights. Our consensus-theoretical methodology begins with the modelling of basic attribute characteristics, mapping them into fuzzy preference relations and thus supports the decision-making process with respect to consensus.