Judgment aggregation and the problem of tracking the truth
Synthese 187 (1):209-221 (2012)
| Abstract | The aggregation of consistent individual judgments on logically interconnected propositions into a collective judgment on those propositions has recently drawn much attention. Seemingly reasonable aggregation procedures, such as propositionwise majority voting, cannot ensure an equally consistent collective conclusion. The literature on judgment aggregation refers to that problem as the discursive dilemma. In this paper, we motivate that many groups do not only want to reach a factually right conclusion, but also want to correctly evaluate the reasons for that conclusion. In other words, we address the problem of tracking the true situation instead of merely selecting the right outcome. We set up a probabilistic model analogous to Bovens and Rabinowicz (2006) and compare several aggregation procedures by means of theoretical results, numerical simulations and practical considerations. Among them are the premise-based, the situation-based and the distance-based procedure. Our findings confirm the conjecture in Hartmann, Pigozzi and Sprenger (2008) that the premise-based procedure is a crude, but reliable and sometimes even optimal form of judgment aggregation. | |||||||||
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Christian List (2012). The Theory of Judgment Aggregation: An Introductory Review. Synthese 187 (1):179-207.
Gabriella Pigozzi (2006). Belief Merging and the Discursive Dilemma: An Argument-Based Account to Paradoxes of Judgment Aggregation. Synthese 152 (2):285 - 298.
Stephan Hartmann, Gabriella Pigozzi & Jan Sprenger (2010). Reliable Methods of Judgment Aggregation. Journal for Logic and Computation 20:603--617.
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.
Stephan Hartmann & Jan Sprenger (2012). Judgment Aggregation and the Problem of Tracking the Truth. Synthese 187 (1):209-221.
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