Reference : Individual Opinions-Based Judgment Aggregation Procedures |
Scientific congresses, symposiums and conference proceedings : Paper published in a book | |||
Engineering, computing & technology : Computer science | |||
http://hdl.handle.net/10993/16098 | |||
Individual Opinions-Based Judgment Aggregation Procedures | |
English | |
Benamara, Farah [> >] | |
Kaci, Souhila [> >] | |
Pigozzi, Gabriella [University of Luxembourg > Faculty of Science, Technology and Communication (FSTC) > Computer Science and Communications Research Unit (CSC) >] | |
2010 | |
Modeling Decisions for Artificial Intelligence | |
Springer | |
Lecture Notes in Computer Science, 6408 | |
55–66 | |
No | |
978-3-642-16291-6 | |
Berlin | |
Germany | |
7th International Conference, MDAI 2010 | |
October 27-29, 2010 | |
Perpignan | |
France | |
[en] Judgment aggregation is a recent formal discipline that studies how to aggregate individual judgments on logically connected propositions to form collective decisions on the same propositions. Despite the apparent simplicity of the problem, the aggregation of individual judgments can result in an inconsistent outcome. This seriously troubles this research field. Expert panels, legal courts, boards, and councils are only some examples of group decision situations that confront themselves with such aggregation problems. So far, the existing framework and procedures considered in the literature are idealized. Our goal is to enrich standard judgment aggregation by allowing the individuals to agree or disagree on the decision rule. Moreover, the group members have the possibility to abstain or express neutral judgments. This provides a more realistic framework and, at the same time, consents the definition of an aggregation procedure that escapes the inconsistent group outcome. | |
http://hdl.handle.net/10993/16098 | |
10.1007/978-3-642-16292-3_8 |
There is no file associated with this reference.
All documents in ORBilu are protected by a user license.