Proceedings of the 2015 Conference of the International Fuzzy Systems Association and the European Society for Fuzzy Logic and Technology

Biased experts and similarity based weights in preferences aggregation

Authors
Gleb Beliakov, Simon James, Laura Smith, Tim Wilkin
Corresponding Author
Gleb Beliakov
Available Online June 2015.
DOI
https://doi.org/10.2991/ifsa-eusflat-15.2015.53How to use a DOI?
Keywords
Aggregation functions, non-monotonic averaging, consensus, pairwise preferences, group decision making, induced OWA.
Abstract
In a group decision making setting, we consider the potential impact an expert can have on the overall ranking by providing a biased assessment of the alternatives that differs substantially from the majority opinion. In the framework of similarity based veraging functions, we show that some alternative approaches to weighting the experts’ inputs during the aggregation process can minimize the influence the biased expert is able to exert.
Open Access
This is an open access article distributed under the CC BY-NC license.

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Cite this article

TY  - CONF
AU  - Gleb Beliakov
AU  - Simon James
AU  - Laura Smith
AU  - Tim Wilkin
PY  - 2015/06
DA  - 2015/06
TI  - Biased experts and similarity based weights in preferences aggregation
BT  - Proceedings of the 2015 Conference of the International Fuzzy Systems Association and the European Society for Fuzzy Logic and Technology
PB  - Atlantis Press
SP  - 363
EP  - 370
SN  - 1951-6851
UR  - https://doi.org/10.2991/ifsa-eusflat-15.2015.53
DO  - https://doi.org/10.2991/ifsa-eusflat-15.2015.53
ID  - Beliakov2015/06
ER  -