Biased experts and similarity based weights in preferences aggregation
Gleb Beliakov, Simon James, Laura Smith, Tim Wilkin
Available Online June 2015.
- https://doi.org/10.2991/ifsa-eusflat-15.2015.53How to use a DOI?
- Aggregation functions, non-monotonic averaging, consensus, pairwise preferences, group decision making, induced OWA.
- 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.
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 -