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Modified Component Valuations in Valuation Based Systems as a Way to Optimize Query Processing

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Abstract

Valuation-Based System (VBS for short) can represent knowledge indifferent domains including probability theory, Dempster-Shafertheory and possibility theory. More recent studies show that theframework of VBS is also appropriate for representing and solvingBayesian decision problems and optimization problems. In this paperafter introducing the valuation based system framework, we presentMarkov-like properties of VBS and a method for resolving queries toVBS.

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References

  • Bertele, U. and Brioschi, F. (1972). Nonserial Dynamic Programming, NY: Academic Press.

    Google Scholar 

  • Clifford, A.H. and Preston, G.B. (1961). The Algebraic Theory of Semigroups, Providence (vol. 1) Rhode Island: American Mathematical Society.

    Google Scholar 

  • 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 

  • 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 

  • Klopotek, M.A. (1994). Beliefs in Markov Trees—From Local Computations to Local Valuation. In R. Trappl (Ed.), Proc. EMCSR’94(vol. 1, pp. 351–358). World Scientific Publishers.

  • Klopotek, M.A. (1995). On (Anti)Conditional Independence in Dempster-Shafer Theory to appear in Journal Mathware and Softcomputing.

  • 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 

  • Pearl, J. (1988). Probabilistic Reasoning in Intelligent Systems: Networks of Plausible Inference, Morgan Kaufman.

  • Shafer, G. (1976). A Mathematical Theory of Evidence, Princeton, NJ: Princeton University Press.

    Google Scholar 

  • Shenoy, P.P. (1989). A Valuation-Based Language for Expert Systems. International Journal of Approximate Reasoning, 3, 383–411.

    Google Scholar 

  • Shenoy, P.P. (1991). Valuation-Based Systems for Discrete Optimization. In P.P. Bonissone, M. Henrion, L.N. Kanal, and J.F. Lemmer (Eds.), Uncertainty in Artificial Intelligence(vol. 6, pp. 385–400), Amsterdam: North-Holland.

    Google Scholar 

  • Shenoy, P.P. (1993). A New Method for Representing and Solving Bayesian Decision Problems. In D.J. Hand ( Ed.), Artificial Intelligence Frontiers in Statistics: AI and Statistics III( pp. 119–138). London: Chapman and Hall.

    Google Scholar 

  • Shenoy, P.P. (1994). Conditional Independence in Valuation-Based Systems. International Journal of Approximate Reasoning, 10, 203–234

    Google Scholar 

  • Shenoy, P.P. and Shafer, G. (1986). Propagating Belief Functions Using Local Computations. IEEE Expert, 1(3), 43–52

    Google Scholar 

  • Thoma, H.M. (1991). Belief Function Computations. In I.R. Goodman et al. ( Eds.), Conditional Logics in Expert Systems( pp. 269–308). North-Holland.

  • Wen, W.X. (1991). From Relational Databases to Belief Networks. In B. D’Ambrosio, Ph. Smets, and P.P. Bonissone ( Eds.), Proc. 7th Conference on Uncertainty in Artificial Intelligence( pp. 406–413). Morgan Kaufmann.

  • Wierzchoń, S.T. (1995). Markov-Like Properties of Joint Valuations, submitted.

  • Wong, S.K., Xiang, Y., and Nie, X. (1993). Representation of Bayesian networks as relational databases. In D. Heckerman and A. Mamdani ( Eds.), Proc. 9th Conference on Uncertainty Artificial Intelligence( pp. 159–165). Morgan Kaufmann.

  • Xu, H. (1995). Computing Marginals for Arbitrary Subsets from Marginal Representation in Markov Trees, Artificial Intelligence, 74, 177–189.

    Google Scholar 

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Wierzchoń, S., Klopotek, M. Modified Component Valuations in Valuation Based Systems as a Way to Optimize Query Processing. Journal of Intelligent Information Systems 9, 157–180 (1997). https://doi.org/10.1023/A:1008651431868

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  • DOI: https://doi.org/10.1023/A:1008651431868

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