Fuzzy Clustering Approach for Non-cooperative Behavior Detection in Consensus Reaching Processes
Ivan Palomares, Luis Martínez, Francisco Herrera
Available Online October 2013.
- https://doi.org/10.2991/.2013.5How to use a DOI?
- Group Decision Making, Consensus Reaching, Preference Relation, Fuzzy Clustering, Behavior Detection
- 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.
- Open Access
- This is an open access article distributed under the CC BY-NC license.
Cite this article
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 - 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 - https://doi.org/10.2991/.2013.5 ID - Palomares2013/10 ER -