PhilSci Archive

Reliable Methods of Judgment Aggregation

Hartmann, Stephan and Pigozzi, Gabriella and Sprenger, Jan (2007) Reliable Methods of Judgment Aggregation. [Preprint]

WarningThere is a more recent version of this item available.
[img]
Preview
PDF
RMJA.pdf

Download (349kB)

Abstract

The aggregation of consistent individual judgments on logically interconnected propositions into a collective judgment on the same 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 such a problem as the discursive dilemma. In this paper we assume that the decision which the group is trying to reach is factually right or wrong. Hence, the question we address in this paper is how good the various approaches are at selecting the right conclusion. We focus on two approaches: distance-based procedures and Bayesian analysis. Under the former we also subsume the conclusion- and premise-based procedures discussed in the literature. Whereas we believe the Bayesian analysis to be theoretically optimal, the distance-based approaches have more parsimonious presuppositions and are therefore easier to apply.


Export/Citation: EndNote | BibTeX | Dublin Core | ASCII/Text Citation (Chicago) | HTML Citation | OpenURL
Social Networking:
Share |

Item Type: Preprint
Creators:
CreatorsEmailORCID
Hartmann, Stephan
Pigozzi, Gabriella
Sprenger, Jan
Keywords: Collective decision theory, judgment aggregation, discursive dilemma
Subjects: Specific Sciences > Probability/Statistics
General Issues > Decision Theory
General Issues > Confirmation/Induction
Specific Sciences > Economics
Depositing User: Stephan Hartmann
Date Deposited: 17 Oct 2007
Last Modified: 07 Oct 2010 15:15
Item ID: 3593
URI: http://philsci-archive.pitt.edu/id/eprint/3593

Available Versions of this Item

Monthly Views for the past 3 years

Monthly Downloads for the past 3 years

Plum Analytics

Actions (login required)

View Item View Item