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On penalty-based aggregation functions and consensus

Beliakov, Gleb, Calvo, Tomasa and James, Simon 2011, On penalty-based aggregation functions and consensus, in Consensual processes, Springer-Verlag, Berlin, Germany, pp.23-40.

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Title On penalty-based aggregation functions and consensus
Author(s) Beliakov, Gleb
Calvo, Tomasa
James, Simon
Title of book Consensual processes
Editor(s) Herrera-Viedma, Enrique
Garcia-Lapresta, José Luis
Kacprzyk, Janusz
Fedrizzi, Mario
Nurmi, Hannu
Zadrozny, Slawomir
Publication date 2011
Series Studies in fuzziness and soft computing; v. 267
Chapter number 2
Total chapters 21
Start page 23
End page 40
Total pages 18
Publisher Springer-Verlag
Place of Publication Berlin, Germany
Keyword(s) penalty-based aggregation functions
Summary The problem of aggregating individual preferences in order to arrive at a group consensus arises naturally in elections where a candidate must be chosen that best represents the individuals’ differing opinions. Other contexts include the judging of sporting competitions and the fusion of sensor readings. In these applications it makes sense that the aggregated result should be as close as possible to the individual inputs, giving rise to the need for methods that minimize this difference. Penalty-based aggregation functions are precisely those functions that aim to accomplish this, drawing upon various notions of “difference” in varying situations.
ISBN 9783642205323
9783642205330
3642205321
ISSN 1434-9922
Language eng
Field of Research 080108 Neural, Evolutionary and Fuzzy Computation
Socio Economic Objective 970108 Expanding Knowledge in the Information and Computing Sciences
HERDC Research category B1 Book chapter
HERDC collection year 2011
Copyright notice ©2011, Springer-Verlag
Persistent URL http://hdl.handle.net/10536/DRO/DU:30043130

Document type: Book Chapter
Collection: School of Information Technology
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