Methods for distance-based judgment aggregation

Abstract Judgment aggregation theory, which concerns the translation of individual judgments on logical propositions into consistent group judgments, has shown that group consistency generally cannot be guaranteed if each proposition is treated independently from the others. Developing the right method of abandoning independence is thus a high-priority goal. However, little work has been done in this area outside of a few simple approaches. To fill the gap, we compare four methods based on distance metrics between judgment sets. The methods generalize the premise-based and sequential priority approaches to judgment aggregation, as well as distance-based preference aggregation. They each guarantee group consistency and implement a range of distinct functions with different properties, broadening the available tools for social choice. A central result is that only one of these methods (not previously considered in the literature) satisfies three attractive properties for all reasonable metrics.
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    Stephan Hartmann & Gabriella Pigozzi (2006). Merging Judgments and the Problem of Truth-Tracking. In Jerome Lang & Ulle Endriss (eds.), Computational Social Choice 2006. University of Amsterdam.

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