Skip to main content

Adding Uncertainty to a Rete-OO Inference Engine

  • Conference paper
Rule Representation, Interchange and Reasoning on the Web (RuleML 2008)

Part of the book series: Lecture Notes in Computer Science ((LNPSE,volume 5321))

Abstract

The RETE algorithm has been used to implement first-order logic based inference engines and its object-oriented extension allows to reason directly over entities rather than predicates. One of the limitations of FOL is its inability to deal with uncertainty, although it exists in many forms and it is typical of the way humans reason. In this paper, the steps of a general uncertain reasoning are outlined, without choosing a specific type or representation of uncertainty. Then, the process is translated into a further extension of the RETE networks, showing a possible architecture allowing a Rete-OO based engine to reason with uncertain rules. This architecture is being implemented in the Drools rule engine.

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

Access this chapter

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 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

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Clips, a tool for building expert systems, http://clipsrules.sourceforge.net/

  2. Jess, the rule engine for java platform, http://www.jessrules.com/

  3. Atanassov, K.T., Koshelev, M., Kreinovich, V., Rachamreddy, B., Yasemis, H.: Fundamental justification of intuitionistic fuzzy logic and of interval-valued fuzzy methods

    Google Scholar 

  4. Cuzzolin, F.: Geometry of dempster’s rule of combination. IEEE Transactions on Systems, Man, and Cybernetics, Part B 34(2), 961–977 (2004)

    Article  Google Scholar 

  5. Damásio, C.V., Pan, J.Z., Stoilos, G., Straccia, U.: An approach to representing uncertainty rules in ruleML. In: Eiter, E.T., Franconi, R., Hodgson, S. (eds.) RuleML, pp. 97–106. IEEE Computer Society, Los Alamitos (2006)

    Google Scholar 

  6. Denoeux,: Reasoning with imprecise belief structures. IJAR: International Journal of Approximate Reasoning 20 (1999)

    Google Scholar 

  7. Doorenbos, R.B.: Production matching for large learning systems. Technical Report CS-95-113, Carnegie Mellon University, School of Computer Science

    Google Scholar 

  8. Dubois, D., Prade, H.: Fuzzy Sets and Systems: Theory and Applications. Academic Press, London (1980)

    MATH  Google Scholar 

  9. Dubois, D., Hüllermeier, E., Prade, H.: A systematic approach to the assessment of fuzzy association rules. Data Min. Knowl. Discov 13(2), 167–192 (2006)

    Article  MathSciNet  Google Scholar 

  10. Boley, H., et al.: Fol ruleml: The first-order logic web language, http://www.ruleml.org/fol/

  11. Proctor, M., et al.: Drools, http://www.jboss.org/drools/

  12. Forgy, C.: Rete: A fast algorithm for the many patterns/many objects match problem. Artif. Intell 19(1), 17–37 (1982)

    Article  Google Scholar 

  13. Hájek, P.: Metamathematics of Fuzzy Logic. Trends in Logic: Studia Logica Library, vol. 4. Kluwer Academic Publishers, Dordrecht (1998)

    MATH  Google Scholar 

  14. Hall, L.O.: Rule chaining in fuzzy expert systems. IEEE-FS 9, 822–828 (2001)

    Google Scholar 

  15. Pan, J.Z., Stamou, G.B., Tzouvaras, V., Horrocks, I.: f-SWRL: A fuzzy extension of SWRL. In: Duch, W., Kacprzyk, J., Oja, E., Zadrożny, S. (eds.) ICANN 2005. LNCS, vol. 3697, pp. 829–834. Springer, Heidelberg (2005)

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2008 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Sottara, D., Mello, P., Proctor, M. (2008). Adding Uncertainty to a Rete-OO Inference Engine. In: Bassiliades, N., Governatori, G., Paschke, A. (eds) Rule Representation, Interchange and Reasoning on the Web. RuleML 2008. Lecture Notes in Computer Science, vol 5321. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-88808-6_13

Download citation

  • DOI: https://doi.org/10.1007/978-3-540-88808-6_13

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-88807-9

  • Online ISBN: 978-3-540-88808-6

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics