Measuring dissimilarity between judgment sets

Abstract

Distances and scores are widely used to measure (dis)similarity between objects of information such as preferences, belief sets, judgment sets, etc. Typically, measures are directly imported from information theory or topology, with little consideration for adequacy in the context of comparing logically related information. We propose a set of desirable properties for measures used to aggregate (logically related) judgments, and show which of the measures used for this purpose satisfy them.