Skip to main content
SpringerLink
Log in

An Efficient Solver for Parametrized Difference Revision

  • Conference paper
  • First Online:
AI 2019: Advances in Artificial Intelligence (AI 2019)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 11919))

Included in the following conference series:

Abstract

We present GenC, an efficient and highly-parallel belief revision solver for paramatrized difference operators. GenC uses an AllSAT solver to enumerate the possible models of a formula, and then determines the output of revision through a series of bit comparisons. The result is a system that can calculate the result of revision for formulas with 100 variables and millions of clauses in just seconds; the running times obtained by GenC far surpass existing solvers for belief revision. The system also has many features that are useful for practical problems: it supports both interactive and offline data entry, it allows multiple formats for entering formulas, and it provides output in human-readable format. Most importantly, GenC is able to model revision by any parametrized difference operator, which allows a wide range of practical problems to be easily captured.

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

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 39.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 54.99
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

References

  1. Alchourrón, C.E., Gärdenfors, P., Makinson, D.: On the logic of theory change: partial meet functions for contraction and revision. J. Symb. Logic 50(2), 510–530 (1985)

    Article  Google Scholar 

  2. Aravanis, T., Peppas, P.: Belief revision in answer set programming. In: Proceedings of the 21st Panhellenic Conference on Informatics (PCI 2017) (2017)

    Google Scholar 

  3. Dalal, M.: Investigations into a theory of knowledge base revision. In: Proceedings of the National Conference on Artificial Intelligence (AAAI), pp. 475–479 (1988)

    Google Scholar 

  4. Delgrande, J.P., Liu, D.H., Schaub, T., Thiele, S.: COBA 2.0: a consistency-based belief change system. In: Mellouli, K. (ed.) ECSQARU 2007. LNCS (LNAI), vol. 4724, pp. 78–90. Springer, Heidelberg (2007). https://doi.org/10.1007/978-3-540-75256-1_10

    Chapter  Google Scholar 

  5. Eiter, T., Gottlob, G.: On the complexity of propositional knowledge base revision, updates and counterfactuals. Artif. Intell. 57(2–3), 227–270 (1992)

    Article  MathSciNet  Google Scholar 

  6. Hoos, H., Stützle, T.: SATLIB: an online resource for research on SAT. In: SAT 2000, pp. 283–292 (2000)

    Google Scholar 

  7. Hunter, A., Tsang, E.: GenB: a general solver for AGM revision. In: Michael, L., Kakas, A. (eds.) JELIA 2016. LNCS (LNAI), vol. 10021, pp. 564–569. Springer, Cham (2016). https://doi.org/10.1007/978-3-319-48758-8_40

    Chapter  Google Scholar 

  8. Hunter, A.: Learning belief revision operators. In: Proceedings of the Canadian Conference on Artificial Intelligence, pp. 239–245 (2018)

    Chapter  Google Scholar 

  9. Katsuno, H., Mendelzon, A.O.: Propositional knowledge base revision and minimal change. Artif. Intell. 52(2), 263–294 (1992)

    MathSciNet  MATH  Google Scholar 

  10. Peppas, P., Williams, M.-A.: Kinetic consistency and relevance in belief revision. In: Michael, L., Kakas, A. (eds.) JELIA 2016. LNCS (LNAI), vol. 10021, pp. 401–414. Springer, Cham (2016). https://doi.org/10.1007/978-3-319-48758-8_26

    Chapter  MATH  Google Scholar 

  11. Toda, T., Soh, T.: Implementing efficient all solutions SAT solvers. ACM J. Exp. Algorithmics 21(1), 1.12:1–1.12:44 (2016)

    MathSciNet  MATH  Google Scholar 

  12. Toda, T., Tsuda, K.: BDD construction for all solutions SAT and efficient caching mechanism. In: Proceedings of the 30th Annual ACM Symposium on Applied Computing, pp. 1880–1886 (2015)

    Google Scholar 

  13. Williams, M.-A.: Applications of belief revision. In: Freitag, B., Decker, H., Kifer, M., Voronkov, A. (eds.) DYNAMICS 1997. LNCS, vol. 1472, pp. 287–316. Springer, Heidelberg (1998). https://doi.org/10.1007/BFb0055503

    Chapter  Google Scholar 

  14. Zhuang, Z., Wang, Z., Wang, K., Qi, G.: DL-lite contraction and revision. J. Artif. Intell. Res. (JAIR) 56, 329–378 (2016)

    Article  MathSciNet  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. BC Institute of Technology, Burnaby, Canada

    Aaron Hunter & John Agapeyev

Authors
  1. Aaron Hunter
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. John Agapeyev
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Aaron Hunter .

Editor information

Editors and Affiliations

  1. University of South Australia, Adelaide, SA, Australia

    Jixue Liu

  2. The University of Melbourne, Melbourne, VIC, Australia

    James Bailey

Rights and permissions

Reprints and permissions

Copyright information

© 2019 Springer Nature Switzerland AG

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Hunter, A., Agapeyev, J. (2019). An Efficient Solver for Parametrized Difference Revision. In: Liu, J., Bailey, J. (eds) AI 2019: Advances in Artificial Intelligence. AI 2019. Lecture Notes in Computer Science(), vol 11919. Springer, Cham. https://doi.org/10.1007/978-3-030-35288-2_12

Download citation

  • DOI: https://doi.org/10.1007/978-3-030-35288-2_12

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-35287-5

  • Online ISBN: 978-3-030-35288-2

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics

Search

Navigation