Aggregation Methods for Fuzzy Judgments

Arrow (1963) established that a group cannot always reach logically consistent collective outcome. Subsequently many developments like premise based, conclusion based and distance based methods have emerged in literature to reach group consistency. This study is focused on the judgment aggregation in fuzzy logic based setting with novel involvement of family of t-norms. We compare three distance based methods due to Miller and Osherson (2009) using Lukasiewicz and min t-norm. These methods in fuzzy logic based settings give closer results to consistency of outcome. It also broaden the set of properties and authenticity of the methods. Distance methods in our study also satisfy Arrow’s axioms in solution method.