Modified component valuations in Valuation Based systems as a way to optimize query processing

  • Slawomir T. Wierzchoń
  • Mieczysław A. Kłopotek
Communications Session 5A Intelligent Information Systems
Part of the Lecture Notes in Computer Science book series (LNCS, volume 1079)


Valuation-Based System can represent knowledge in different domains including probability theory, Dempster-Shafer theory and possibility theory. More recent studies show that the framework of VBS is also appropriate for representing and solving Bayesian decision problems and optimization problems.

In this paper, after introducing the valuation based system (VBS) framework, we present Markov-like properties of VBS and a method for resolving queries to VBS.


Approximate Reasoning Knowledge Representation and Integration valuation based systems query processing graphical representation of domain knowledge 


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. 1.
    Cooper, G.F., and Herskovits, E., (1992). A Bayesian method for the induction of probabilistic networks from data. Machine Learning, 9:309–347.Google Scholar
  2. 2.
    Jensen, F.V., Lauritzen, S.L., and Olesen, K.G., (1990). Bayesian updating in causal probabilistic networks by local computations. Computational Statistics Quarterly, 4: 269–282.Google Scholar
  3. 3.
    Klopotek, M.A., (1994). Beliefs in Markov Trees — From Local Computations to Local Valuation. In: R. Trappl, Ed.: Cybernetics and Systems Research, World Scientific Publishers, Vol.1, pp. 351–358.Google Scholar
  4. 4.
    Lauritzen, S.L., and Spiegelhalter, D.J., (1988). Local computation with probabilities on graphical structures and their application to expert systems. J. Roy. Stat. Soc., B50: 157–244.Google Scholar
  5. 5.
    Pearl, J. (1988). Probabilistic Reasoning in Intelligent Systems: Networks of Plausible Inference. Morgan Kaufman.Google Scholar
  6. 6.
    Shafer, G. (1976) A Mathematical Theory of Evidence, Princeton University Press, Princeton, NJ.Google Scholar
  7. 7.
    Shenoy, P.P. (1989) A valuation-based language for expert systems, International Journal of Approximate Reasoning, 3:383–411.Google Scholar
  8. 8.
    Shenoy, P.P. (1991) Valuation-based systems for discrete optimization, Uncertainty in AI 6, (P.P. Bonissone et al., eds), North-Holland, Amsterdam, pp. 385–400.Google Scholar
  9. 9.
    Shenoy, P.P. (1993) A new method for representing and solving Bayesian decision problems, Artificial Intelligence Frontiers in Statistics: AI and Statistics III (D.J. Hand, ed.), Chapman & Hall, London, pp.119–138.Google Scholar
  10. 10.
    Shenoy, P.P. (1994). Conditional independence in valuation-based systems, International Journal of Approximate Reasoning, 10:203–234.Google Scholar
  11. 11.
    Shenoy, P.P., and Shafer, G. (1986). Propagating belief functions using local computations. IEEE Expert, 1(3), 43–52.Google Scholar
  12. 12.
    Thoma, H.M., (1991). Belief function computations, in: I.R. Goodman et al (Eds.), Conditional Logics in Expert Systems, North-Holland, pp. 269–308Google Scholar
  13. 13.
    Wierzchoń, S.T., (1995). Markov-like properties of joint valuations, submitted.Google Scholar
  14. 14.
    Wen, W.X., (1991). From relational databases to belief networks, in: B.D'Ambrosio, Ph. Smets, and P.P. Bonissone (Eds.), Proc. 7-th Conference on Uncertainty in AI, Morgan Kaufmann, pp. 406–413.Google Scholar
  15. 15.
    Wong, S.K., Xiang, Y., and Nie, X., (1993). Representation of Bayesian networks as relational databases, in: D. Heckerman, and A. Mamdani, (Eds.), Proc. 9-th Conference on Uncertainty in AI, Morgan Kaufmann, pp. 159–165.Google Scholar
  16. 16.
    Xu, H., (1995). Computing marginals for arbitrary subsets from marginal representation in Markov trees, Artificial Intelligence, 74, 177–189.Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 1996

Authors and Affiliations

  • Slawomir T. Wierzchoń
    • 1
  • Mieczysław A. Kłopotek
    • 1
  1. 1.Institute of Computer SciencePolish Academy of SciencesWarszawaPoland

Personalised recommendations