Skip to main content
Springer Nature Link
Log in

Similarity-Based Equality with Lazy Evaluation

  • Conference paper
Information Processing and Management of Uncertainty in Knowledge-Based Systems. Theory and Methods (IPMU 2010)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 80))

  • 1020 Accesses

Abstract

Thanks to the high expressive power and the rule-based nature of declarative languages, their influences are growing in the fields of AI, knowledge representation, and so on. On the other hand, since the notion of “equality” plays a crucial role on such languages, in this paper we focus in the design of a flexible (fuzzy) but efficient (lazy) notion of equality for hybrid declarative languages amalgamating functional-fuzzy-logic features. Here, we show that, by extending at a very low cost the notion of “strict equality” typically used in lazy functional-logic languages (Curry, Toy), and by relaxing it to the more flexible one of similar equality used in fuzzy-logic programming languages (Likelog, Bousi~Prolog), similarity relations can be successfully treated while mathematical functions are lazily evaluated in a given program. Our method represents a very easy, low-cost way, for fuzzifying lazy functional-logic languages and it can be implemented at a very high abstraction level by simply performing a static pre-process at compilation time which only manipulates the program at a syntactic level (i.e., the underlying operational mechanism based on rewriting/narrowing remains untouched).

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

Access this chapter

Log in via an institution

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

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. Arcelli, F., Formato, F.: Likelog: A logic programming language for flexible data retrieval. In: Proc. of the ACM Symposium on Applied Computing (SAC 1999). Artificial Intelligence and Computational Logic, pp. 260–267. ACM, New York (1999)

    Chapter  Google Scholar 

  2. Baldwin, J.F., Martin, T.P., Pilsworth, B.W.: Fril- Fuzzy and Evidential Reasoning in Artificial Intelligence. John Wiley & Sons, Inc., Chichester (1995)

    Google Scholar 

  3. Guerrero, J.A., Moreno, G.: Optimizing fuzzy logic programs by unfolding, aggregation and folding. ENTCS (Elsevier Science) 219, 19–34 (2008)

    MATH  Google Scholar 

  4. Hanus, M. (ed.): Curry: An Integrated Functional Logic Language (2003), http://www.informatik.uni-kiel.de/~mh/curry

  5. Ishizuka, M., Kanai, N.: Prolog-ELF Incorporating Fuzzy Logic. In: Joshi, A.K. (ed.) Proc. of IJCAI 1985, pp. 701–703. Morgan Kaufmann, San Francisco (1985)

    Google Scholar 

  6. Julián, P., Moreno, G., Penabad, J.: On Fuzzy Unfolding. A Multi-Adjoint Approach. Fuzzy Sets and Systems 154, 16–33 (2005)

    Article  MathSciNet  MATH  Google Scholar 

  7. Julián, P., Rubio, C., Gallardo, J.: Bousi~prolog: a prolog extension language for flexible query answering. ENTCS (Elsevier Science) 248, 131–147 (2009)

    Google Scholar 

  8. Julián-Iranzo, P.: A procedure for the construction of a similarity relation. In: Verdegay, J.L., Magdalena, L., Ojeda-Aciego, M. (eds.) Proc. of the 12th Int. Conf. on Information Processing and Management of Uncertainty in Knwoledge-based Systems, IPMU 2008, U. Málaga, pp. 489–496 (2008)

    Google Scholar 

  9. Lee, R.C.T.: Fuzzy Logic and the Resolution Principle. Journal of the ACM 19(1), 119–129 (1972)

    Article  MathSciNet  MATH  Google Scholar 

  10. Li, D., Liu, D.: A fuzzy Prolog database system. John Wiley & Sons, Inc., Chichester (1990)

    Google Scholar 

  11. Lloyd, J.W.: Foundations of Logic Programming. Springer, Berlin (1987)

    Book  MATH  Google Scholar 

  12. Loogen, R., López-Fraguas, F., Rodríguez-Artalejo, M.: A Demand Driven Computation Strategy for Lazy Narrowing. In: Penjam, J., Bruynooghe, M. (eds.) PLILP 1993. LNCS, vol. 714, pp. 184–200. Springer, Heidelberg (1993)

    Google Scholar 

  13. Medina, J., Ojeda-Aciego, M., Vojtáš, P.: Similarity-based unification: a multi-adjoint approach. Fuzzy Sets and Systems 146(1), 43–62 (2004)

    Article  MathSciNet  MATH  Google Scholar 

  14. Morcillo, P.J., Moreno, G.: Programming with Fuzzy Logic Rules by using the FLOPER Tool. In: Bassiliades, N., Governatori, G., Paschke, A. (eds.) RuleML 2008. LNCS, vol. 5321, pp. 119–126. Springer, Heidelberg (2008)

    Chapter  Google Scholar 

  15. Moreno, G.: Building a Fuzzy Transformation System. In: Wiedermann, J., Tel, G., Pokorný, J., Bieliková, M., Štuller, J. (eds.) SOFSEM 2006. LNCS, vol. 3831, pp. 409–418. Springer, Heidelberg (2006)

    Chapter  Google Scholar 

  16. Moreno, G., Pascual, V.: A hybrid programming scheme combining fuzzy-logic and functional-logic resources. Fuzzy Sets and Systems 160(10), 1402–1419 (2009)

    Article  MathSciNet  MATH  Google Scholar 

  17. Moreno-Navarro, J.J., Rodríguez-Artalejo, M.: Logic Programming with Functions and Predicates: The language Babel. Journal of Logic Programming 12(3), 191–224 (1992)

    Article  MATH  Google Scholar 

  18. Nguyen, H.T., Walker, E.A.: A First Course in Fuzzy Logic. Chapman & Hall/CRC, Boca Ratón (2000)

    MATH  Google Scholar 

  19. Sessa, M.I.: Approximate reasoning by similarity-based SLD resolution. Fuzzy Sets and Systems 275, 389–426 (2002)

    MathSciNet  MATH  Google Scholar 

  20. Zadeh, L.A.: Similarity relations and fuzzy orderings. Informatica Science 3, 177–200 (1971)

    Article  MathSciNet  MATH  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Department of Computing Systems, U. Castilla-La Mancha, 02071, Albacete, Spain

    Ginés Moreno

Authors
  1. Ginés Moreno
    View author publications

    You can also search for this author in PubMed Google Scholar

Editor information

Editors and Affiliations

  1. Fachbereich Mathematik und Informatik, Philipps-Universität Marburg, Marburg, Germany

    Eyke Hüllermeier

  2. Department of Knowledge Processing and Language Engineering, Otto-von-Guericke University of Magdeburg, Universitätsplatz 2, 39106, Magdeburg, Germany

    Rudolf Kruse

  3. Fakultät für Elektrotechnik und Informationstechnik, Technische Universität Dortmund, 44221, Dortmund, Germany

    Frank Hoffmann

Rights and permissions

Reprints and permissions

Copyright information

© 2010 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Moreno, G. (2010). Similarity-Based Equality with Lazy Evaluation. In: Hüllermeier, E., Kruse, R., Hoffmann, F. (eds) Information Processing and Management of Uncertainty in Knowledge-Based Systems. Theory and Methods. IPMU 2010. Communications in Computer and Information Science, vol 80. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-14055-6_12

Download citation

  • DOI: https://doi.org/10.1007/978-3-642-14055-6_12

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-14054-9

  • Online ISBN: 978-3-642-14055-6

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics