MULTI-AGENT VOTING FOR CONFLICT RESOLUTION - A Fuzzy Approach

Miklos Nagy, Maria Vargas-Vera

2010

Abstract

Software agents that interpret the possible meaning of SemanticWeb data differently should be able to resolve their differences i.e. resolve conflicts effectively. One typical use case is ontology mapping where different agents using different similarity measures create beliefs in the assessed similarities, which needs to be combined into a more coherent state. The combination of these contradicting beliefs can easily worsen the mapping precision and recall, which leads to poor performance of any ontology mapping algorithm. In these scenarios agents, which use different similarities and combine them into a more reliable and coherent view can easily become unreliable when these contradictions are not managed effectively between the different agents. In this paper we propose a solution based on the fuzzy voting model for managing such situations by introducing trust and voting between software agents that resolve contradicting beliefs in the assessed similarities.

References

  1. Austen-Smith, D. and Banks, J. S. (1996). Information aggregation, rationality, and the condorcet jury theorem. The American Political Science Review, 90(1):34-45.
  2. Batini, C., Lenzerini, M., and Navathe, S. B. (1986). A comparative analysis of methodologies for database schema integration. ACM Computing Surveys, 18(4):323-364.
  3. Beckett, D. (2004). Rdf/xml syntax specification, http://www.w3.org/rdf/.
  4. Euzenat, J. and Shvaiko, P. (2007). Ontology matching. Springer-Verlag, Heidelberg (DE).
  5. Ferrara, A., Lorusso, D., Stamou, G., Stoilos, G., Tzouvaras, V., and Venetis, T. (2008). Resolution of conflicts among ontology mappings: a fuzzy approach. In Proceedings of the 3rd International Workshop on Ontology Matching.
  6. Jean-Mary, Y. R. and Kabuka, M. R. (2008). Asmov: Results for oaei 2008. In Proceedings of the 3rd International Workshop on Ontology Matching.
  7. Liu, X.-J., Wang, Y.-L., and Wang, J. (2006). Towards a semi-automatic ontology mapping - an approach using instance based learning and logic relation mining. In Fifth Mexican International Conference (MICAI 2006) on Artificial Intelligence.
  8. McGuinness, D. L. and Harmelen, F. V. (2004). Owl web ontology language, http://www.w3.org/tr/owlfeatures/.
  9. Miles, A. and Bechhofer, S. (2008). Skos simple knowledge organization system, http://www.w3.org/tr/skosreference/.
  10. Nagy, M., Vargas-Vera, M., and Motta, E. (2008). Managing conflicting beliefs with fuzzy trust on the semantic web. In The 7th Mexican International Conference on Artificial Intelligence (MICAI 2008).
  11. Shvaiko, P. and Euzenat, J. (2008). Ten challenges for ontology matching. Technical Report DISI-08-042, University of Trento.
  12. Tang, J., Li, J., Liang, B., Huang, X., Li, Y., and Wang, K. (2006). Using bayesian decision for ontology mapping. Web Semantics: Science, Services and Agents on the World Wide Web, 4(243-262).
  13. Wand, Y. and Wang, R. Y. (1996). Anchoring data quality dimensions in ontological foundations. Communications of the ACM, pages 86-95.
  14. Wang, R. Y., Kon, H. B., and Madnick, S. E. (1993). Data quality requirements analysis and modeling. In Proceedings of the Ninth International Conference on Data Engineering, pages 670-677.
  15. Young, H. P. (1988). Condorcet's theory of voting. The American Political Science Review, 82(4):1231-1244.
Download


Paper Citation


in Harvard Style

Nagy M. and Vargas-Vera M. (2010). MULTI-AGENT VOTING FOR CONFLICT RESOLUTION - A Fuzzy Approach . In Proceedings of the 2nd International Conference on Agents and Artificial Intelligence - Volume 1: ICAART, ISBN 978-989-674-021-4, pages 178-183. DOI: 10.5220/0002701301780183


in Bibtex Style

@conference{icaart10,
author={Miklos Nagy and Maria Vargas-Vera},
title={MULTI-AGENT VOTING FOR CONFLICT RESOLUTION - A Fuzzy Approach},
booktitle={Proceedings of the 2nd International Conference on Agents and Artificial Intelligence - Volume 1: ICAART,},
year={2010},
pages={178-183},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0002701301780183},
isbn={978-989-674-021-4},
}


in EndNote Style

TY - CONF
JO - Proceedings of the 2nd International Conference on Agents and Artificial Intelligence - Volume 1: ICAART,
TI - MULTI-AGENT VOTING FOR CONFLICT RESOLUTION - A Fuzzy Approach
SN - 978-989-674-021-4
AU - Nagy M.
AU - Vargas-Vera M.
PY - 2010
SP - 178
EP - 183
DO - 10.5220/0002701301780183