A universal model of knowledge conflict resolving using consensus methods in multi-agent decision support systems

• Authors: Andrzej Bytniewski , Marcin Hernes , Kamal Matouk
• Languages of publication: EN

Abstracts

EN

The article presents a proposition of a universal model of knowledge conflict resolving using consensus methods, which can be used in a multi-agent decision support system. Knowledge conflicts often appear, when individual agents generate different solutions of the same problem. It is very difficult for the user – decision-maker to make a good decision because the analysis of solutions generated by agents is very time-consuming and the decision must be made quickly. Moreover, selecting one of the decisions on the basis of the experience of the decision-maker is very risky, because he/she could choose the worst solution. Consensus methods, however, allow to agree, on the basis of the solutions generated by agents, one solution, which is a compromise. As a consequence, reducing the time and decreasing the risk level of the decision taking process, to enable the functioning of the enterprise in more flexible.

Keywords

EN

decision support systems; knowledge conflicts; multi-agent systems; consensus methods

• Publisher: Wydawnictwo Uniwersytetu Ekonomicznego we Wrocławiu
• Journal: Informatyka Ekonomiczna
• Year: 2013
• Issue: 4(30)
• Pages: 82-90

Contributors

author

Andrzej Bytniewski

• Wroclaw University of Economics

author

Marcin Hernes

• Wroclaw University of Economics

author

Kamal Matouk

• Wroclaw University of Economics

References

• Badica C., Ganzha M., Gawinecki M., Kobzdej P., Paprzycki M., Towards trust management in an agent-based e-commerce system – initial consideration, [in:] A. Zgrzywa (ed.), Multimedia and Network Information Systems, Wroclaw University of Technology Press, Wroclaw 2006, pp. 225-237.
• Bytniewski A. (ed.), Architecture of Integrated Management Information Systems, Wroclaw University of Economics Press, Wroclaw 2005.
• Ferber J., Multi-Agent Systems. An Introduction to Artificial Intelligence, Addison Wesley, New York 1999.
• Hernes M., Nguyen N.T., Deriving consensus for hierarchical incomplete ordered partitions and coverings, “Journal of Universal Computer Science” 2007, 13(2), pp. 317-328.
• Katarzyniak R., Nguyen N.T., Using consensus methods to determining encapsulated profiles of the world states distributed in multiagent systems, [in:] Proceedings of 14th International Conference on System Science, Coventry 2000, pp. 300-304.
• Kisielnicki J., Management Information Systems, Placet Press, Warsaw 2008.
• Korczak J., Hernes M., Bac M., Risk avoiding strategy in multi-agent trading system, [in:] Annals of Computer Science and Information Systems, Proceedings of Federated Conference Computer Science and Information Systems (FedCSIS), Krakow 2013, pp. 1119-1126.
• Kubiak B.F., Knowledge and intellectual capital – management strategy in Polish organizations, [in:] B.F. Kubiak, A. Korowicki (eds.), Information Management, Gdansk University Press, Gdansk 2009, pp. 16-24.
• Matouk K., Business Intelligence solution for accounting, [in:] A. Bytniewski (ed.), Influence of Network Technology on the Organization and Functioning of Information Management Systems, Wroclaw University of Economics Press, Wroclaw 2006, pp. 36-44.
• Nguyen N.T., Using consensus methodology in processing inconsistency of knowledge, [in:] M. Last et al. (eds.), Advances in Web Intelligence and Data Mining, series Studies in Computational Intelligence, Springer-Verlag, 2006, pp. 161-170.
• Sobieska-Karpińska J., Hernes M., Consensus determining algorithm in multiagent decision support system with taking into consideration improving agent’s knowledge, [in:] Proceedings of Federated Conference Computer Science and Information Systems (FedCSIS), Wrocław 2012, pp. 1035-1040.
• Sobieska-Karpińska J., Hernes M., The postulates of consensus determining in financial decision support systems, [in:] Annals of Computer Science and Information Systems, Proceedings of Federated Conference Computer Science and Information Systems (FedCSIS), Kraków 2013, pp. 1165-1168.
• Sobieska-Karpińska J., Hernes M., Value of information in distributed decision support system, [in:] M. Pańkowska (ed.), Infonomics for Distributed Business and Decision-Making Environments: Creating Information System Ecology, IGI Global, New York, Hershey 2010, pp. 153-176.
• Subba Reddy N.V., Nagabhushan P., A connectionist expert system model for conflict resolution in unconstrained handwritten numeral recognition, Mysore: Department of Computer Science and ngineering, S.J. College of Engineering, 1997, pp. 161-169.
• Yager R., Approximate Reasoning and Conflict Resolution, Machine Intelligence Institute, Iona College, 2000, pp. 15-42.
• Zgrzywa M., Consensus determining with dependencies of attributes with interval values, “Journal of Universal Computer Science” 2007, vol. 13, no. 2, pp. 329-344.