Network engineering for agile belief network models

IEEE Transactions on Knowledge and Data Engineering

Volumn 12, Issue 4, 2000, Pages 487-498

  Laskey, Kathryn Blackmond ^a,b   Mahoney, Suzanne M ^c  

^a IEEE   (United States)

^b George Mason University   (United States)

^c Information Extraction and Transport Inc   (United States)

Author keywords

Agile modeling; Belief networks; Elicitation; Knowledge representation; Rapid prototyping; Systems engineering

Indexed keywords

COMPUTER SIMULATION; KNOWLEDGE ACQUISITION; KNOWLEDGE BASED SYSTEMS; NEURAL NETWORKS; NUMERICAL METHODS; PROBABILITY DISTRIBUTIONS; RANDOM PROCESSES; RAPID PROTOTYPING; SYSTEMS ANALYSIS; SYSTEMS ENGINEERING;

AGILE MODELING; BELIEF NETWORKS; NETWORK ENGINEERING; SEMANTIC INFORMATION;

KNOWLEDGE REPRESENTATION;

EID: 0034215587     PISSN: 10414347     EISSN: None     Source Type: Journal    
DOI: 10.1109/69.868902     Document Type: Article

References (40)

1. L. Adelman, Evaluating Decision Support and Expert Systems. New York: John Wiley & Sons, 1992.
2. B. Beizer, Software System Testing and Quality Assurance. New York:Van Nostrand Reinhold, 1984.
3. B.S. Blanchard and W.J. Fabrycky, Systems Engineering and Analysis. Englewood Cliffs, N.J.: Prentice Hall, 1990.
4. B.W. Boehm, "A Spiral Model of Software Development and Enhancement," Computer, vol. 21, no. 5, pp. 61-72, 1988.
5. E. Charniak and R. Goldman, "A Semantics for Probabilistic Quantifier-Free First-Order Languages, with Particular Application to Story Understanding," Proc. Int'l Joint Conf. Artificial Intelligence, 1989.
6. B. D'Ambrosio, "Local Expression Languages for Probabilistic Dependence," Proc. Ninth Conf. Uncertainty in Artificial Intelligence, 1995.
7. W. Edwards and F.H. Barron, "SMARTS and SMARTER: Improved Simple Methods for Multiattribute Utility Measurement," Organizational Behavior and Human Decision Processes, vol. 60, pp. 306-325, 1994.
8. A. Gelman, J. Carlin, H. Stern, and D. Rubin, Bayesian Data Analysis. Chapman and Hall, 1995.
9. J.D.F. Habbema, J. Hilden, and B. Bjerregaard, "The Measurement of Performance in Probabilistic Diagnosis I-IV," Methods of Information in Medicine, 1978.
10. A.D. Hall, "Three Dimensional Morphology of Systems Engineering," IEEE Trans. Systems, Man, and Cybernetics, vol. 5, no. 2, pp. 156-160, 1969.
11. D. Heckerman, Probabilistic Similarity Networks. Cambridge, Mass.: MIT Press, 1991.
12. J.S. Hodges, "Six (or So) Things You Can Do with a Bad Model," Operations Research, vol. 39, p. 3, 1991.
13. J.S. Hodges and J.A. Dewar, Is It You or Your Model Talking? A Framework for Model Validation, Rand Publication Series, R-4114-AF/A/OSD, 1992.
14. R. Howard and J. Matheson, "Influence Diagrams" Readings on the Principles and Applications of Decision Analysis, Strategic Decisions Group, R. Howard, and J. Matheson, eds., vol. 2, pp. 721-762, 1981.
15. F.V. Jensen, Bayesian Networks. New York: Springer, 1996.
16. F.V. Jensen, B. Chamberlain, T. Nordahl, and F. Jensen, "Analysis in HUGIN of Data Conflict," Proc. Sixth Conf. Uncertainty in Artificial Intelligence, 1990.
17. R. Goldman and E. Charniak, "Dynamic Construction of Belief Networks," Proc. Sixth Conf. Uncertainty in Artificial Intelligence, 1990.
18. P. Haddawy, "Generating Bayesian Networks from Probability Logic Knowledge Bases," Proc. 10th Conf. Uncertainty in Artificial Intelligence, 1994.
19. M. Henrion, M. Pradhan, B. Del Favero, K. Huang, G. Provan, and P. O'Rorke, "Why Is Diagnosis Using Belief Networks Insensitive to Imprecision in Probabilities?" Proc. 12th Conf. Uncertainty in Artificial Intelligence, pp. 307-314, 1996.
20. D. Koller and A. Pfeffer, "Object-Oriented Bayesian Networks" Proc. 13th Conf. Uncertainty in Artificial Intelligence, D. Geiger, and P. Shenoy, eds., 1997.
21. K.B. Laskey, "Sensitivity Analysis for Probability Assessments in Bayesian Networks," IEEE Trans. Systems, Man, and Cybernetics, vol. 25, no. 6, pp. 901-909, 1995.
22. K.B. Laskey, "Conflict and Surprise: Heuristics for Model Revision," Proc. Seventh Conf. Uncertainty in Artificial Intelligence, B.D. D'Ambrosio, P. Smets, and P.P. Bonissone eds., 1991.
23. S.M. Mahoney and K.B. Laskey, "Constructing Situation Specific Networks," Proc. 14th Conf. Uncertainty in Artificial Intelligence, G. Cooper, and S. Moral, eds., 1998.
24. S.M. Mahoney and K.B. Laskey, "Representing and Combining Partially Specified CPTs," Proc. 14th Conf. Uncertainty in Artificial Intelligence, K. Laskey, and H. Prade, eds., 1999.
25. K.B. Laskey and S.M. Mahoney, "Network Fragments: Representing Knowledge for Constructing Probabilistic Models.," Proc. 13th Conf. Uncertainty in Artificial Intelligence, D. Geiger, and P. Shenoy, eds., 1997.
26. M.G. Morgan, M. Henrion, and M. Small, Uncertainty: A Guide to Dealing with Uncertainty in Quantitative Risk and Policy Analysis. New York: Cambridge Univ. Press, 1990.
27. K.C. Ng and B. Abramson, "A Sensitivity Analysis of Pathfinder: A Follow-Up Study," Proc. Seventh Conf. Uncertainty in Artificial Intelligence, 1991.
28. R.M. O'Keefe, O. Balci, and E.P. Smith, "Validating Expert System Performance," IEEE Expert, vol. 4, pp. 81-89, 1987.
29. J. Pearl, Probabilistic Reasoning in Intelligent Systems: Networks of Plausible Inference. San Mateo, Calif.: Morgan Kaufmann, 1988.
30. D. Poole, "Probabilistic Horn Abduction," Artificial Intelligence, vol. 64, no. 1, pp. 81-129, 1993.
31. M. Pradhan, G. Provan, B. Middleton, and M. Henrion, "Knowledge Engineering for Large Belief Networks," Proc. 10th Conf. Uncertainty in Artificial Intelligence, pp. 484-490, 1994.
32. G. Provan, "Abstraction in Belief Networks: The Role of Intermediate States in Diagnostic Reasoning," Proc. Seventh Conf. Uncertainty in Artificial Intelligence, pp. 464-471, 1995.
33. A. Sage, Systems Engineering. New York: John Wiley & Sons 1992.
34. C.S. Spetzler and C.-A.S. Staël von Holstein, "Probability Encoding in Decision Analysis," Management Science, vol. 22, no. 3, 1975.
35. D.J. Spiegelhalter and R.P. Knill-Jones, "Statistical and Knowledge-Based Approaches to Clinical Decision Support Systems, with an Application to Gastroenterology," J. Royal Statistical Soc., vol. 147, pp. 35-77, 1984.
36. S. Srinivas, "A Generalization of the Noisy-OR Model," Proc. Ninth Conf. Uncertainty in Artificial Intelligence, 1993.
37. H.J. Suermondt, "Explanation in Bayesian Belief Networks," PhD dissertation, Report STAN-CS-92-1417, Depts. of Computer Science and Medicine, Stanford Univ., Stanford, Calif., 1992.
38. J.J. Weiss, "Importance Analysis Measure," IET Report, Aug. 1995.
39. D. von Winterfeldt and W. Edwards, Decision Analysis and Behavioral Research. Cambridge, U.K.: Cambridge Univ. Press, 1986.
40. D. Kahneman and A. Tversky, Judgment under Uncertainty: Heuristics and Biases. New York: Cambridge Univ. Press, 1982.