Skip to main content
SpringerLink
Log in

A programmable approach to revising knowledge bases

  • Published:
Science in China Series F: Information Sciences Aims and scope Submit manuscript

Abstract

This paper presents a programmable approach to revising knowledge bases consisting of clauses. Some theorems and lemmas are shown in order to give procedures for generating maximally consistent subsets. Then a complete procedure and an incomplete procedure for generating the maximal consistent subsets are presented, and the correctness of the procedures is also shown. Furthermore, a way to implement knowledge base revision is presented, and a prototype system is introduced. Compared with related works, the main characteristic of our approach is that the approach can be implemented by a computer program.

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

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Similar content being viewed by others

References

  1. Doyle, J., A truth maintenance system, Artificial Intelligence, 1979, 12: 231–272.

    Article  MathSciNet  Google Scholar 

  2. Kleer, J. D., An assumption-based TMS, Artificial Intelligence, 1986, 28: 127–162.

    Article  Google Scholar 

  3. Fagin, R., Ullman, J. D., Vardi, M. Y., On the semantics of updates in databases, in Proceedings of the Second ACM SIGACT-SIGMOD Symposium on Principle of Database Systems, Atlanta, Georgia, USA, 1983, 352–365.

  4. Ginsberg, M. L., Smith, D. E., Reasoning about Action I:a Possible Worlds Approach, Artificial Intelligence, 1988, 35: 165–195.

    Article  MATH  MathSciNet  Google Scholar 

  5. Alchourron, C. E., Gärdenfors, P., Markinson, D., On the logic of theory change: Partial meet contraction and revision functions, Journal of Symbolic Logic, 1985, 50(2): 510–530.

    Article  MATH  MathSciNet  Google Scholar 

  6. Gärdenfors, P., Knowledge in Flux: Modeling the Dynamics of Epistemic States, Cambridge: The MIT Press, 1988.

    Google Scholar 

  7. Gärdenfors, P., Makinson, D., Revisions of knowledge systems using epistemic entrenchment, in Proceedings of the Second Conference on Theoretical Aspects of Reasoning About Knowledge, Asilomar, California, USA, 1988, 83–95.

  8. Friedman, N., Halpern, J. Y., Modeling belief in dynamic systems Part II: Revision and update, Journal of Artificial Intelligence Research, 1999, 10: 117–167.

    MATH  MathSciNet  Google Scholar 

  9. Katsuno, H., Mendelzon, A. O., Propositional knowledge base revision and minimal change, Artificial Intelligence, 1991, 52: 263–294.

    Article  MATH  MathSciNet  Google Scholar 

  10. Nebel, B., A knowledge level analysis of belief revision, in Proceedings of the First International Conference on Principles of Knowledge Representation and Reasoning, Mrogan Kaufman, 1989, 301–311.

  11. Hansson, S. O., New operators for theory change, Theoria, 1989, 50: 114–132.

    MathSciNet  Google Scholar 

  12. Fuhrman, A., Theory contraction through base contraction, Journal of Philosophical Logic, 1991, 20: 175–203.

    Article  MathSciNet  Google Scholar 

  13. Rott, H., A nonmonotonic conditional logic for belief revision I, in The Logic of Theory Change (eds. Fuhrman, A., Morreau, M.), Berlin: Springer-Verlag, 1991, 135–181.

    Chapter  Google Scholar 

  14. Williams, M. A., Two operators for theory base change, in Proceedings of the Fifth Australian Joint Conference on Artificial Intelligence, Hobart, Australia, 1992, 256–265.

  15. Wobcke, W. R., A belief revision approach to nonmonotonic reasoning, in Proceedings of the Fifth Australian Joint Conference on Artificial Intelligence, Hobart, Australia, 1992, 278–283.

  16. Li, W., An open logic system, Science in China, Ser. A (in Chinese), 1993, 22(10): 1103–1113.

    Google Scholar 

  17. Li Wei, A development calculus for specifications, Science in China, Ser. F, 2003, 46(5): 390–400.

    Article  MATH  Google Scholar 

  18. Darwiche, A., Pearl, J., On the logic of iterated belief revision, Artificial Intelligence, 1997, 89(1&2): 1–29.

    Article  MATH  MathSciNet  Google Scholar 

  19. Boutilier, C., Revision sequences and nested conditionals, in Proceedings of International Conference on Artificial Intelligence, Toronto, Ontario, Canada, 1993, 519–525.

  20. Dixon, S. E., Wocke, W. R., The implementation of a first-order logic AGM belief revision system, in Proceedings of the Thirteenth International Joint Conference on Artificial Intelligence, Chambery, France, 1993, 534–539.

  21. Williams, M. A., Towards a practical approach to belief revision: Reason-based approach, in Proceedings of the Fifth International Joint Conference on Principles of Knowledge Representation and Reasoning, Morgan Kaufmann, 1996, 412–421.

  22. Damásio, C. V., Nejdl, W., Pereira, L. P., REVISE: An extended logic programming systems for revising knowledge bases, in Proceedings of the International Conference on Knowledge Representation and Reasoning, Bonn, Germany, 1994, 607–618.

  23. Yuan, L. Y., You, J. H., Coherence approach to logic program revision, IEEE Transactions on Knowledge and Data Engineering, 1998, 10(1): 108–119.

    Article  Google Scholar 

  24. Kaplan, A. N., Schubert, L. K., A computational model of belief, Artificial Intelligence, 2000, 120: 119–160.

    Article  MATH  MathSciNet  Google Scholar 

  25. Rodrigues, O., Benevides, M., Belief revision in pseudo-definite sets, in Proceedings of the XI Brazilian Symposium on Artificial Intelligence, Fortaleza, Brazil, 1994, 157–171.

  26. Nayak, A. C., Pagnucco, M., Pappas, P., Dynamic belief revision operators, Artificial Intelligence, 2003, 146: 193–228.

    Article  MATH  MathSciNet  Google Scholar 

  27. Sullivan, J. W., Tyler, S. W., Intelligent User Interfaces, New York: ACM Press, 1991.

    MATH  Google Scholar 

  28. Gallier, J. H., Logic for Computer Science, Foundations of Automatic Theorem Proving, New York: John Wilsey & Sons, 1987.

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Institute of Software, Chinese Academy of Sciences, 100080, Beijing, China

    Luan Shangmin & Dai Guozhong

  2. Department of Computer Science and Technology, Beijing University of Aeronautics and Astronautics, 100083, Beijing, China

    Li Wei

Authors
  1. Luan Shangmin
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Dai Guozhong
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Li Wei
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Luan Shangmin.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Luan, S., Dai, G. & Li, W. A programmable approach to revising knowledge bases. Sci China Ser F 48, 681–692 (2005). https://doi.org/10.1360/03yf0327

Download citation

  • Received:

  • Revised:

  • Issue Date:

  • DOI: https://doi.org/10.1360/03yf0327

Keywords

Search

Navigation