Sensitivity analysis in influence diagrams

IEEE Transactions on Systems, Man, and Cybernetics Part A:Systems and Humans.

Volumn 33, Issue 2, 2003, Pages 223-234

  Nielsen, Thomas Dyhre ^a   Jensen, Finn V ^a  

^a AALBORG UNIVERSITY   (Denmark)

Author keywords

Influence diagrams; Probability parameters; Sensitivity analysis; Utility parameters

Indexed keywords

ALGORITHMS; DECISION MAKING; PROBABILITY; SENSITIVITY ANALYSIS;

INFLUENCE DIAGRAMS (ID);

CYBERNETICS;

EID: 0041877643     PISSN: 10834427     EISSN: None     Source Type: Journal    
DOI: 10.1109/TSMCA.2003.811116     Document Type: Article

References (30)

1. R. A. Howard and J. E. Matheson, "Influence diagrams," in The Principles and Applications of Decision Analysis, R. A. Howard and J. E. Matheson, Eds: Strategic Decision Group, 1981, vol. 2, ch. 37, pp. 721-762.
2. K. L. Poh and E. J. Horvitz, "Reasoning about the value of decision-model refinement: Methods and applications," in Proc. 9th Conf. Uncertainty Artificial Intelligence, D. Heckerman and A. Mamdani, Eds. San Mateo, CA: Morgan Kaufmann, 1993.
3. J. C. Felli and G. B. Hazen, "Do sensitivity analysis really capture problem sensitivity? An empirical analysis based on information value," Risk, Decision and Policy, vol. 4, no. 2, pp. 79-98, 1999.
4. C. Skaanning, "A knowledge acquisition tool for Bayesian-network troubleshooters," in Proc. 16th Conf. Uncertainty Artificial Intelligence, C. Boutilier and M. Goldszmidt, Eds. San Mateo, CA: Morgan Kaufmann, 2000, pp. 549-557.
5. K. Blackmond Laskey, "Sensitivity analysis for probability assessments in Bayesian networks," IEEE Trans. Syst., Man, Cybern., vol. SMC-25, pp. 901-909, June 1995.
6. E. Castillo, J. M. Gutierrez, and A. S. Hadi, "Sensitivity analysis in discrete Bayesian networks," IEEE Trans. Syst., Man, Cybern., A, vol. 27, pp. 412-423, July 1997.
7. U. Kjærulff and L. C. van der Gaag, "Making sensitivity analysis computationally efficient," in Proc. 16th Conf. Uncertainty Artificial Intelligence, C. Boutilier and M. Goldszmidt, Eds. San Mateo, CA: Morgan Kaufmann, 2000, pp. 317-325.
8. V. M. H. Coupé, "Sensitivity analysis of decision-theoretic networks," Ph.D. dissertation, Dept. Public Health, Erasmus Univ. Rotterdam, 3000 DR Rotterdam, The Netherlands, 2000.
9. F. Jensen, F. V. Jensen, and S. L. Dittmer, "From influence diagrams to junction trees," in Proc. 10th Conf. Uncertainty Artificial Intelligence, R. Lopez de Mantaras and D. Poole, Eds. San Mateo, CA: Morgan Kaufmann, 1994, pp. 367-373.
10. D. Nilsson and S. L. Lauritzen, "Evaluating influence diagrams using LIMIDs," in Proc. 16th Conf. Uncertainty Artificial Intelligence, C. Boutilier and M. Goldszmidt, Eds., 2000, pp. 436-345.
11. P. P. Shenoy, "Valuation-based systems for Bayesian decision analysis," Oper. Res., vol. 40, no. 3, pp. 463-484, 1992.
12. R. D. Shachter, "Evaluating influence diagrams," Oper. Res. Soc. Amer., vol. 34, no. 6, pp. 79-90, Feb. 1986.
13. J. A. Tatman and R. D. Shachter, "Dynamic programming and influence diagrams," IEEE Trans. Syst., Man, Cybern., vol. 20, pp. 365-379, Mar./Apr. 1990.
14. F. V. Jensen, Bayesian Networks and Decision Graphs. New York: Springer-Verlag, 2001.
15. A. L. Madsen and F. V. Jensen, "Lazy evaluation of symmetric Bayesian decision problems," in Proc. 15th Conf. Uncertainty Artificial Intelligence, K. B. Laskey and H. Prade, Eds. San Mateo, CA: Morgan Kaufmann, 1999, pp. 382-390.
16. T. D. Nielsen and F. V. Jensen, "Welldefined decision scenarios," in Proc. 15th Conf. Uncertainty Artificial Intelligence, K. B. Laskey and H. Prade, Eds. San Mateo, CA: Morgan Kaufmann, 1999, pp. 502-511.
17. R. D. Shachter, "Efficient value of information computation," in Proc. 15th Conf. Uncertainty Artificial Intelligence, K. B. Laskey and H. Prade, Eds. San Mateo, CA: Morgan Kaufmann, 1999, pp. 594-601.
18. D. Nilsson and F. V. Jensen, "Probabilities of future decisions," in Proc. Int. Conf. Informational Processing Management Uncertainty Knowledge-Based Systems, 1998, pp. 1454-1461.
19. C. Bielza, D. Ríos-Insua, and S. Ríos-Insua, "Influence diagrams under partial information," in Bayesian Statistics 5. New York: Oxford Univ. Press, 1996, pp. 491-497.
20. P. Doubilet, C. B. Begg, M. C. Weinstein, P. Braun, and B. J. McNeil, "Probabilistic sensitivity analysis using Monte Carlo simulation," Med. Dec. Making, vol. 5, no. 2, pp. 157-177, 1985.
21. J. C. Felli and G. B. Hazen, "Sensitivity analysis and the expected value of perfect information," Med. Dec. Making, vol. 18, pp. 95-109, 1998.
22. G. F. Cooper and E. Herskovits, "A Bayesian method for constructing Bayesian belief networks from databases," in Proc. 7th Conf. Uncertainty Artificial Intelligence, B. D. D'Ambrosio, P. Smets, and P. P. Bonissone, Eds., 1991, pp. 86-94.
23. C. Bielza, S. Ríos-Insua, M. Gómez, and J. A. Fernández del Pozo, "Sensitivity analysis in IctNeo," in Robust Bayesian Analysis, ser. Lecture Notes in Statistics. New York: Springer-Verlag, 2000, vol. 152, pp. 317-334.
24. H. Wang and M. J. Druzdzel, "User interface tools for navigating in conditional probability tables and elicitation of probabilities in Bayesian networks," in Proc. 16th Conf. Uncertainty Artificial Intelligence, C. Boutilier and M. Goldszmidt, Eds. San Mateo, CA: Morgan Kaufmann, 2000, pp. 617-625.
25. E. Castillo, J. M. Gutiérrez, and A. S. Hadi, "A new method for efficient symbolic propagation in discrete Bayesian networks," Networks, vol. 28, pp. 31-43, 1996.
26. M. R. McCord and R. de Neufville, "Utility dependence on probability: An empirical demonstration," J. Large Scale Syst., vol. 6, pp. 91-103, 1984.
27. U. Chajewska and D. Koller, "Utilities as random variables: Density estimation and structure discovery," in Proc. 16th Conf. Uncertainty Artificial Intelligence, C. Boutilier and M. Goldszmidt, Eds., 2000, pp. 63-71.
28. S. L. Dittmer and F. V. Jensen, "Myopic value of information in influence diagrams," in Proc. 13th Conf. Uncertainty Artificial Intelligence, D. Geiger and P. P. Shenoy, Eds. San Mateo, CA: Morgan Kaufmann, 1997.
29. A. Cano, S. Moral, and A. Salmerón, "Penniless propagation in join trees," Int. J. Intell. Syst., vol. 15, pp. 1027-1059, 2000.
30. G. Wu and R. Gonzalez, "Curvature of the probability weighting function," Manage. Sci., vol. 42, no. 12, pp. 1676-1690, 1996.