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Journal of Logic and Computation Advance Access originally published online on May 2, 2008
Journal of Logic and Computation 2009 19(3):461-473; doi:10.1093/logcom/exn011
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© The Author, 2008. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oxfordjournals.org

This article appears in the following Journal of Logic and Computation issue: Special Issue: Connections between Belief Revision, Belief Merging and Social Choice [View the issue table of contents]

Original Articles

Aggregating Judgements by Merging Evidence

Jon Williamson

University of Kent. E-mail: j.williamson{at}kent.ac.uk


  Abstract

The theory of belief revision and merging has recently been applied to judgement aggregation. In this article I argue that judgements are best aggregated by merging the evidence on which they are based, rather than by directly merging the judgements themselves. This leads to a three-step strategy for judgement aggregation. First, merge the evidence bases of the various agents using some method of belief merging. Second, determine which degrees of belief one should adopt on the basis of this merged evidence base, by applying objective Bayesian theory. Third, determine which judgements are appropriate given these degrees of belief by applying a decision-theoretic account of rational judgement formation.

Keywords: Judgement aggregation; belief merging; belief revision; objective Bayesianism; decision theory; maximum entropy


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