Name
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. |
Year | DOI | Venue |
|---|---|---|
2009 | 10.1093/logcom/exn011 | J. Log. Comput. |
Keywords | Field | DocType |
merging evidence,three-step strategy,aggregating judgements,merged evidence base,judgement aggregation,objective bayesian theory,evidence base,various agent,rational judgement formation,decision-theoretic account,belief revision | Judgement,Artificial intelligence,Merge (version control),Mathematics,Belief revision,Bayesian probability | Journal |
Volume | Issue | ISSN |
19 | 3 | 0955-792X |
Citations | PageRank | References |
1 | 0.37 | 14 |
Authors | ||
1 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| jon williamson | 1 | 38 | 11.42 |