Fuzzy Clustering Approach for Non-cooperative Behavior Detection in Consensus Reaching Processes

DOI

10.2991/.2013.5How to use a DOI?

Keywords

Group Decision Making, Consensus Reaching, Preference Relation, Fuzzy Clustering, Behavior Detection

Abstract

Consensus reaching processes in group decision making attempt to reach a mutual agreement amongst experts before making a common decision. Classical consensus models are focused on problems where few decision makers participate. However, new societal and technological trends may require a large number of experts in such processes. In group decision making problems involving large groups, identifying and dealing with experts who present noncooperative behaviors during the consensus reaching process might become a particularly complex task. Such behaviors might bias the discussion process and prevent achieving an agreement. This paper presents a fuzzy clustering-based approach to detect and manage non-cooperative behaviors. Such an approach is integrated into a consensus model suitable to manage large groups of experts in group decision making problems.

Copyright

© 2013, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Ivan Palomares
AU  - Luis Martínez
AU  - Francisco Herrera
PY  - 2013/10
DA  - 2013/10
TI  - Fuzzy Clustering Approach for Non-cooperative Behavior Detection in Consensus Reaching Processes
BT  - Proceedings of the Fourth International Workshop on Knowledge Discovery, Knowledge Management and Decision Support
PB  - Atlantis Press
SP  - 37
EP  - 44
SN  - 1951-6851
UR  - https://doi.org/10.2991/.2013.5
DO  - 10.2991/.2013.5
ID  - Palomares2013/10
ER  -