Belief merging has been an active research field with many important applications. Many approaches for belief merging have been proposed, but these approaches only take the belief bases as inputs without the adequate attention to the role of agents, who provide the belief bases, thus the results achieved are merely ideal and difficult to apply in the multi-agent systems. In this paper, we present a merging approach based on the negotiation techniques. A new model is proposed in which agents gradually build their common belief base from the beliefs that they provide in each round of negotiation. A set of postulates is also introduced to characterize the logical properties of the merging results.


Belief merging Belief Negotiation 


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. 1.
    Baral, C., Kraus, S., Minker, J.: Combining multiple knowledge bases. IEEE Trans. on Knowl. and Data Eng. 3, 208–220 (1991)CrossRefGoogle Scholar
  2. 2.
    Baral, C., Kraus, S., Minker, J., Subrahmanian, V.S.: Combining knowledge bases consisting of first order theories. In: Raś, Z.W., Zemankova, M. (eds.) ISMIS 1991. LNCS, vol. 542, pp. 92–101. Springer, Heidelberg (1991)CrossRefGoogle Scholar
  3. 3.
    Benferhat, S., Dubois, D., Kaci, S., Prade, H.: Possibilistic merging and distance-based fusion of propositional information. Annals of Mathematics and Artificial Intelligence 34, 217–252 (2002)MathSciNetCrossRefzbMATHGoogle Scholar
  4. 4.
    Booth, R.: A negotiation-style framework for non-prioritised revision. In: Proceedings of the 8th Conference on Theoretical Aspects of Rationality and Knowledge, TARK 2001, pp. 137–150. Morgan Kaufmann Publishers Inc., San Francisco (2001)Google Scholar
  5. 5.
    Booth, R.: Social contraction and belief negotiation. Inf. Fusion 7, 19–34 (2006)CrossRefGoogle Scholar
  6. 6.
    Everaere, P., Konieczny, S., Marquis, P.: Conflict-based merging operators. In: KR, pp. 348–357 (2008)Google Scholar
  7. 7.
    Konieczny, S.: Belief base merging as a game. Journal of Applied Non-Classical Logics 14(3), 275–294 (2004)CrossRefzbMATHGoogle Scholar
  8. 8.
    Konieczny, S., Lang, J., Marquis, P.: Da2 merging operators. Artif. Intell. 157, 49–79 (2004)CrossRefzbMATHGoogle Scholar
  9. 9.
    Konieczny, S., Pérez, R.P.: Merging information under constraints: a logical framework, vol. 12, pp. 773–808 (2002)Google Scholar
  10. 10.
    Levi, I.: Subjunctives, dispositions and chances. Synthese 34, 423–455 (1977)CrossRefzbMATHGoogle Scholar
  11. 11.
    Liberatore, P., Schaerf, M.: Arbitration (or how to merge knowledge bases). IEEE Trans. on Knowl. and Data Eng. 10, 76–90 (1998)CrossRefGoogle Scholar
  12. 12.
    Lin, J.: Integration of weighted knowledge bases. Artif. Intell. 83, 363–378 (1996)MathSciNetCrossRefGoogle Scholar
  13. 13.
    Qi, G., Liu, W., Bell, D.A.: Merging stratified knowledge bases under constraints. In: Proceedings of the 21st National Conference on Artificial Intelligence, vol. 1, pp. 281–286. AAAI Press, Menlo Park (2006)Google Scholar
  14. 14.
    Revesz, P.Z.: On the semantics of arbitration. International Journal of Algebra and Computation 7, 133–160 (1995)MathSciNetCrossRefzbMATHGoogle Scholar
  15. 15.
    Zhang, D.: A logic-based axiomatic model of bargaining. Artif. Intell. 174, 1307–1322 (2010)MathSciNetCrossRefzbMATHGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  • Trong Hieu Tran
    • 1
  • Quoc Bao Vo
    • 1
  • Ryszard Kowalczyk
    • 1
  1. 1.Swinburne University of TechnologyHawthornAustralia

Personalised recommendations