From knowledge bases to decision models

The Knowledge Engineering Review

Volumn 7, Issue 1, 1992, Pages 35-53

  Wellman, Michael P ^a   Breese, John S ^b   Goldman, Robert P ^c  

^a AIR FORCE RESEARCH LABORATORY   (United States)

^b ROCKWELL SCIENCE CENTER   (United States)

^c TULANE UNIVERSITY   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

EID: 84972347653     PISSN: 02698889     EISSN: 14698005     Source Type: Journal    
DOI: 10.1017/S0269888900006147     Document Type: Article

References (65)

1. Bacchus, F., 1990. Representing and Reasoning with Probabilistic Knowledge: A Logical Approach to Probabilities MIT Press.
2. Breese, J.S., and Horvitz, E.J., 1990. “Ideal reformulation of belief networks” Proceedings of the Sixth Conference on Uncertainty in Artificial Intelligence, Cambridge, MA, July, 64–72.
3. Breese, J.S., 1990. Construction of belief and decision networks, Technical Memorandum 30, Rockwell International Science Center, Palo Alto, CA, January. To appear in Computational Intelligence.
4. Buede, D.M., 1986. “Structuring value attributes” Interfaces 16(2) 52–62.
5. Charniak, E., and McDermott, D., 1985. Introduction to Artificial Intelligence Addison-Wesley.
6. Clark, D.A., Fox, J., Glowinski, A.J. and O’Neil, M.J., 1990. “Symbolic reasoning for decision making” Contemporary Issues in Decision Making Elsevier Science Publishers.
7. Cooper, G.F., and Herskovits, E., 1991. “A Bayesian method for constructing Bayesian belief networks from databases” Proceedings of the Seventh Conference on Uncertainty in Artificial Intelligence, Los Angeles, CA, 86–94.
8. D’Ambrosio, B., and Fehling, M., 1989. “Resource-bounded agents in an uncertain world” AAAI Spring Symposium on Artificial Intelligence and Limited Rationality, 13–17.
9. Dean, T., and Boddy, M., 1988. “An analysis of time-dependent planning” Proceedings of the National Conference on Artificial Intelligence, 49–54.
10. Fertig, K.W., and Breese, J.S., 1989. “Interval influence diagrams” Proceedings of the Workshop on Uncertainty in Artificial Intelligence, Windsor, ON, 102–111.
11. Fox, J., 1991. “Decision theory and autonomous systems” Decision Support Systems and Qualitative Reasoning North-Holland.
12. Geiger, D., Paz, A., and Pearl, J., 1990. “Learning causal trees from dependence information” Proceedings of the National Conference on Artificial Intelligence, Boston, MA, 770–776.
13. Geman, S., and Geman, D., 1984. “Stochastic relaxation, Gibbs distributions and the Bayesian restoration of images” IEEE Transactions on Pattern Analysis and Machine Intelligence 6, 721–741.
14. Goldman, R.P., and Charniak, E., 1990. “Dynamic construction of belief networks” Proceedings of the Sixth Conference on Uncertainty in Artificial Intelligence, Cambridge, MA, 90–97.
15. Goldman, R.P., 1990. “A probabilistic approach to language understanding” Technical Report CS-90-34, Brown University Department of Computer Science, December.
16. Haddawy, P., and Hanks, S., 1990. “Issues in decision-theoretic planning: Symbolic goals and numeric utilities” Proceedings of the DARPA Workshop on Innovative Approaches to Planning, Scheduling, and Control, 48–58.
17. Haddawy, P and Rendell, L., 1990. “Planning and decision theory”, Knowledge Engineering Review 5, 15–33.
18. Haddawy, P., 1991. “A temporal probability logic for representing actions” Principles of Knowledge Representation and Reasoning: Proceedings of the Second International Conference, 313–324.
19. Halpern, J.Y., 1990. “An analysis of first-order logics of probability” Artificial Intelligence 46, 311–350.
20. Hanks, S.J., 1990. “Projecting plans for uncertain worlds” Technical Report YALEU/CSD/RR 756, Yale University Department of Computer Science, January.
21. Hansson, O., Mayer, A., and Russell, S., 1990. “Decision-theoretic planning in BPS” AAAI Symposium on Planning in Uncertain, Unpredictable, or Changing Environments, Available as report, University of Maryland Systems Research Center.
22. Heckerman, D.E., Horvitz, E.J. and Nathwani, B.N., “Toward normative expert systems: The Pathfinder project” Methods of Information in Medicine.
23. Henrion, M., and Druzdzel, M.J., 1990. “Qualitative propagation and scenario-based approaches to explanation of probabilistic reasoning” Proceedings of the Sixth Conference on Uncertainty in Artificial Intelligence, Cambridge, MA, 10–20.
24. Hobbs, J.R., Stickel, M., Martin, P. and Edwards, D., 1988. “Interpretation as abduction” Proceedings of the 26th Annual Meeting of the ACL, 95–103.
25. Holtzman, S., 1989. Intelligent Decision Systems Addison-Wesley.
26. Horvitz, E.J., Breese, J.S. and Henrion, M., 1988. “Decision theory in expert systems and artificial intelligence” International Journal of Approximate Reasoning 2, 247–302.
27. Horvitz, E.J., 1988. Reasoning under varying and uncertain resource constraints” in: Proceedings of the National Conference on Artificial Intelligence, 111–116.
28. Howard, R.A., and Matheson, J.E., 1984b. “Influence diagrams” The Principles and Applications of Decision Analysis, 719–762.
29. Howard, R.A., and Matheson, J.E., 1984. The Principles and Applications of Decision Analysis, Strategic Decisions Group.
30. Kanazawa, K., 1991. “A logic and time nets for probabilistic inference” Proceedings of the National Conference on Artificial Intelligence, Anaheim, CA, 360–365.
31. Keeney, R.L., and Raiffa, H., 1976. Decisions with Multiple Objectives: Preferences and Value Tradeoffs John Wiley.
32. Keeney, R.L., 1986. “Identifying and structuring values” Decision analysis series report, University of Southern California, Los Angeles, CA, December.
33. Langlotz, C.P., Shortliffe, E.H., and Fagan, L.M., 1988. “A methodology for generating computer-based of decision-theoretic advice” Medical Decision Making 8, 290–303.
34. Laskey, K.B., 1990. “A probabilistic reasoning environment” in: Proceedings of the Sixth Conference on Uncertainty in Artificial Intelligence, Cambridge, MA, 415–422.
35. Laskey, K.B., 1991. “Conflict and surprise: Heuristics for model revision” in: Proceedings of the Seventh Conference on Uncertainty in Artificial Intelligence, Los Angeles, CA, 197–204.
36. Lehner, P.E. and Adelman, L., 1990. “Behavioural decision theory and its implication for knowledge engineering” Knowledge Engineering Review 5, 5–14.
37. Leong, T.Y., 1991. “Knowledge representation for supporting decision model formulation in medicine” Technical Report 504, MIT Laboratory for Computer Science, Cambridge, MA, May.
38. Leong, T.Y., 1991. “Representation requirements for supporting decision model formulation” Proceedings of the Seventh Conference on Uncertainty in Artificial Intelligence, Los Angeles, CA, 212–219.
39. Levitt, T.S., Binford, T.O. and Ettinger, G.J., 1990. “Utility based control for computer vision”, Uncertainty in Artificial Intelligence 4, 407–422 Elsevier Science.
40. Loui, R.P., 1989. “Defeasible decisions: What the proposal is and isn’t” Proceedings of the Workshop on Uncertainty in Artificial Intelligence Windsor, ON, 245–252.
41. Nayak, P.P., Joskowicz, L., and Addanki, S., 1991. “Automated model selection using context-dependent behaviors” Fifth International Workshop on Qualitative Physics, Austin, TX, May.
42. Neapolitan, R.E., 1990. Probabilistic Reasoning in Expert Systems: Theory and Algorithms John Wiley.
43. Pearl, J., Geiger, D., and Verma, T., 1989. “Conditional independence and its representations” Kybernetika 25, 33–44.
44. Pearl, J., 1988. Probabilistic Reasoning in Intelligent Systems: Networks of Plausible Inference, Morgan Kaufmann.
45. Pereira, F.C.N., and Warren, D.H.D., 1980. “Definite clause grammars for language analysis—A survey of the formalism and comparison with augmented transition networks” Artificial Intelligence 13, 231–278.
46. Poole, D., 1991. “Representing Bayesian networks within probabilistic Horn abduction” Proceedings of the Seventh Conference on Uncertainty in Artificial Intelligence, Los Angeles, CA, 271–278.
47. Provan, G.M.A., 1991. “Dynamic network updating techniques for diagnostic reasoning” Proceedings of the Seventh Conference on Uncertainty in Artificial Intelligence, Los Angeles, CA, 279–286.
48. Raiffa, H., 1968. Decision Analysis: Introductory Lectures on Choices Under Uncertainty, Addison-Wesley.
49. Reiter, R., 1987. “A theory of diagnosis from first principles” Artificial Intelligence 32, 57–96.
50. Russell, S., and Wefald, E., 1991. Do the Right Thing: Studies in Limited Rationality MIT Press.
51. Saffiotti, A., 1990. “A hybrid framework for representing uncertain knowledge” Proceedings of the National Conference on Artificial Intelligence, Boston, MA, 653–658.
52. Savage, L.J., 1972. The Foundations of Statistics, Dover Publications.
53. Shachter, R.D., 1986. “Evaluating influence diagrams” Operations Research 34, 871–882.
54. Shachter, R.D., 1988. “Probabilistic inference and influence diagrams” Operations Research 36, 589–604.
55. Smith, D.E., 1988. “A decision-theoretic approach to the control of planning search” Technical Report LOGIC-87-11, Department of Computer Science, Stanford University, January.
56. Vilain, M.B., 1985. “The restricted language architecture of a hybrid representation system” in: Proceedings of the Ninth International Joint Conference on Artificial Intelligence, 547–551.
57. Weld, D.S., and Kleer, J., 1989. Readings in Qualitative Reasoning About Physical Systems Morgan Kaufmann.
58. Weld, D.S., 1991. “Reasoning about model accuracy” Technical Report 91-05-02, Department of Computer Science and Engineering, University of Washington, June.
59. Wellman, M.P., and Doyle, J., 1991. “Preferential semantics for goals” Proceedings of the National Conference on Artificial Intelligence, Anaheim, CA, 698–703.
60. Wellman, M.P. and Henrion, M., 1991. “Qualitative intercausal relations, or Explaining ‘explaining away’” Principles of Knowledge Representation and Reasoning: Proceedings of the Second International Conference, 535–546.
61. Wellman, M.P., Eckman, M.H., Fleming, C., Marshall, S.L., Sonnenberg, F.A., and Pauker, S.G., 1989. “Automated critiquing of medical decision trees” Medical Decision Making 9, 272–284.
62. Wellman, M.P., 1986. “Representing health outcomes for automated decision formulation” MEDINFO 86: Proceedings of the Fifth Conference on Medical Informatics, 789–793, Washington, October.
63. Wellman, M.P., 1990. Formulation of Tradeoffs in Planning Under Uncertainty Pitman.
64. Wellman, M.P., 1990. “Fundamental concepts of qualitative probabilistic networks” Artificial Intelligence 44, 257–303.
65. Yen, J., and Bonissone, P.P., 1990. “Extending term subsumption systems for uncertainty management” Proceedings of the Sixth Conference on Uncertainty in Artificial Intelligence, Cambridge, MA, 468–473.