A new distance function for consensus determination in decision support systems
Marcin Hernes , Jadwiga Sobieska-Karpińska , Adrianna Kozierkiewicz , Marcin Pietranik
AbstractConsensus methods are used mainly to solve conflicts of knowledge in decision support systems. Generally speaking, conflicts of knowledge arise from the fact that system nodes (for example, agents, experts) may present various decisions or solutions to the user. This may be due to the use of various methods of decision support or different information sources by agents/experts. If there is a conflict of knowledge in the system and they are not automatically resolving the system cannot generate the final decision, and hence - the decision maker will not receive hints from the system. The use of consensus methods eliminates this problem, because they enable to solve conflicts of knowledge in near real time. At the same time they guarantee the achievement of a good compromise. However, the effective determination of consensus depends, among other, on the correct definition of the distance function. The aim of this paper is to develop a new distance function between the decisions generated by expert of agents in decision support systems.
|Publication size in sheets||0.5|
|Book||Nguyen Ngoc Thanh, Pimenidis Elias , Khan Zaheer , Trawiński Bogdan (eds.): Computational Collective Intelligence. 10th International Conference, ICCCI 2018, Bristol, UK, September 5-7, 2018, Proceedings, Part I, Lecture Notes in Artificial Intelligence, no. 11055, 2018, Springer International Publishing, ISBN 9783319984421, 563 p., DOI:10.1007/978-3-319-98443-8|
|Keywords in English||Knowledge Conflicts, Consensus Methods, Decision Support Systems, Distance Functions|
|Citation count*||1 (2020-01-18)|
* presented citation count is obtained through Internet information analysis and it is close to the number calculated by the Publish or Perish system.