Nothing Special   »   [go: up one dir, main page]

Skip to main content

A Comparison of Merging Operators in Possibilistic Logic

  • Conference paper
Knowledge Science, Engineering and Management (KSEM 2010)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 6291))

Abstract

In this paper, we compare some important merging operators in possibilistic logic. We first introduce semantic merging operators and adaptive merging operators in possibilistic logic. We then propose an approach to evaluating the discriminating power of these merging operators. After that, we analyze the computational complexity of these possibilistic merging operators. Finally, we consider the compatibility of possibilistic merging operators with propositional merging operators.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Subscribe and save

Springer+ Basic
$34.99 /Month
  • Get 10 units per month
  • Download Article/Chapter or eBook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 84.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 109.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

Similar content being viewed by others

References

  1. Amgoud, L., Kaci, S.: An argumentation framework for merging conflicting knowledge bases. IEEE Transactions on Knowledge and Data Engineering 3(2), 208–220 (2007)

    MathSciNet  Google Scholar 

  2. Benferhat, S., Cayrol, C., Dubois, D., Lang, L., Prade, H.: Inconsistency management and prioritized syntax-based entailment. In: Proc. of IJCAI 1993, pp. 640–645 (1993)

    Google Scholar 

  3. Benferhat, S., Dubois, D., Prade, H.: From semantic to syntactic approaches to information combination in possibilistic logic. In: Aggregation and Fusion of Imperfect Information, pp. 141–151. Physica Verlag, Heidelberg (1997)

    Google Scholar 

  4. 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)

    Article  MATH  MathSciNet  Google Scholar 

  5. Benferhat, S., Kaci, S.: Fusion of possibilistic knowledge bases from a postulate point of view. Int. J. Approx. Reasoning 33(3), 255–285 (2003)

    Article  MATH  MathSciNet  Google Scholar 

  6. Benferhat, S., Dubois, D., Prade, H., Williams, M.-A.: A practical approach to fusing prioritized knowledge bases. In: Barahona, P., Alferes, J.J. (eds.) EPIA 1999. LNCS (LNAI), vol. 1695, pp. 223–236. Springer, Heidelberg (1999)

    Chapter  Google Scholar 

  7. Benferhat, S., Sossai, C.: Reasoning with multiple-source information in a possibilistic logic framework. Information Fusion 7(1), 80–96 (2006)

    Google Scholar 

  8. Dubois, D., Prade, H.: Representation and combination of uncertainty with belief functions and possibility measures. Computational Intelligence 4, 244–264 (1988)

    Article  Google Scholar 

  9. Dubois, D., Prade, H., Testemale, C.: Weighted fuzzy pattern matching. Fuzzy Sets and Systems 28, 313–331 (1988)

    Article  MATH  MathSciNet  Google Scholar 

  10. Dubois, D., Prade, H.: Possibility theory and data fusion in poorly informed enviroments. Control Engineering Practice 2(5), 811–823 (1994)

    Article  Google Scholar 

  11. Dubois, D., Fargier, H., Prade, H.: Multiple source information fusion: a practical inconsistency tolerant approach. In: Proc. of IPMU 2000, pp. 1047–1054 (2000)

    Google Scholar 

  12. Dubois, D., Prade, H.: Combination of fuzzy information in the framework of possibility theory. In: Abidi, M.A., Gonzalez, R.C. (eds.) Data Fusion in Robotics and Machine Intelligence, pp. 481–505 (1992)

    Google Scholar 

  13. Dubois, D., Prade, H.: Possibility theory and data fusion in poorly informed enviroments. Control Engineering Practice 2(5), 811–823 (1994)

    Article  Google Scholar 

  14. Dubois, D., Lang, J., Prade, H.: Possibilistic logic. In: Handbook of Logic in Artificial Intelligence and Logic Programming, vol. 3, pp. 439–513. Oxford University Press, Oxford (1994)

    Google Scholar 

  15. Eiter, T., Gottlob, G.: On the compleixty of propositional knowledge base revision, updates, and counterfactuals. Artificial Intelligence 57, 227–270 (1992)

    Article  MATH  MathSciNet  Google Scholar 

  16. Hartley, R.: Transmission of information. Bell System Technical Journal 7, 535–563 (1928)

    Google Scholar 

  17. Higashi, M., Klir, G.: Measures of uncertainty and information based on possibility distribusions. International Journal of General Systems 9(1), 43–58 (1983)

    Article  MathSciNet  Google Scholar 

  18. Johnson, D.S.: A catalog of complexity classes. In: van Leeuwen, J. (ed.) Handbook of Theoretical Computer Science, pp. 67–161 (1990)

    Google Scholar 

  19. Konieczny, S., Pino Pérez, R.: On the logic of merging. In: Proc. of KR 1998, pp. 488–498 (1998)

    Google Scholar 

  20. Konieczny, S.: On the difference between merging knowledge bases and combining them. In: Proc. of KR 2000, pp. 135–144 (2000)

    Google Scholar 

  21. Konieczny, S., Pino Pérez, R.: Merging information under constraints: A logical framework. Journal of Logic and Computation 12(5), 773–808 (2002)

    Article  MATH  MathSciNet  Google Scholar 

  22. Konieczny, S., Lang, J., Marquis, P.: DA2 merging operators. Artificial Intelligence 157(1-2), 49–79 (2004)

    Article  MATH  MathSciNet  Google Scholar 

  23. Liberatore, P., Schaerf, M.: Arbitration (or How to Merge Knowledge Bases). IEEE Transactions on Knowledge and Data Engineering 10(1), 76–90 (1998)

    Article  Google Scholar 

  24. Qi, G., Liu, W., Glass, D.H.: Combining individually inconsistent prioritized knowledge bases. In: Proc. of NMR 2004, pp. 342–349 (2004)

    Google Scholar 

  25. Qi, G., Liu, W., Bell, D.A.: Combining multiple knowledge bases by negotiation: A possibilistic approach. In: Godo, L. (ed.) ECSQARU 2005. LNCS (LNAI), vol. 3571, pp. 501–513. Springer, Heidelberg (2005)

    Chapter  Google Scholar 

  26. Qi, G., Liu, W., Glass, D.H., Bell, D.A.: A split-combination approach for merging possibilistic knowledge bases. Annals of Mathematics and Artificial Intelligence 48(1-2), 45–84 (2006)

    Article  MATH  MathSciNet  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2010 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Qi, G., Liu, W., Bell, D. (2010). A Comparison of Merging Operators in Possibilistic Logic. In: Bi, Y., Williams, MA. (eds) Knowledge Science, Engineering and Management. KSEM 2010. Lecture Notes in Computer Science(), vol 6291. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-15280-1_7

Download citation

  • DOI: https://doi.org/10.1007/978-3-642-15280-1_7

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-15279-5

  • Online ISBN: 978-3-642-15280-1

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics