Decomposition of influence diagrams

Lecture Notes in Artificial Intelligence (Subseries of Lecture Notes in Computer Science)

Volumn 2143, Issue , 2001, Pages 144-155

  Nielsen, Thomas D ^a  

^a AALBORG UNIVERSITY   (Denmark)

Author keywords

[No Author keywords available]

Indexed keywords

DECISION MAKING;

DECISION PROBLEMS; DECISION VARIABLES; INFLUENCE DIAGRAM; OPTIMAL POLICIES; REDUNDANT VARIABLES; SUB-PROBLEMS;

PROBLEM SOLVING;

EID: 84937391107     PISSN: 03029743     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1007/3-540-44652-4_14     Document Type: Conference Paper

References (14)

1. Dan Geiger, Thomas Verma, and Judea Pearl. Dseparation: From theorems to algorithms. In Uncertainty in Artificial Intelligence 5, 1990.
2. Eric Horwitch and Matthew Barry. Display of information for time-critical decision making. In Philippe Besnard and Steve Hanks, editors, Proceedings of the Eleventh Conference on Uncertainty in Artificial Intelligence, pages 296-305. Morgan Kauf- mann Publishers, 1995.
3. Ronald A. Howard and James E. Matheson. Influence diagrams. In Ronald A. Howard and James E. Matheson, editors, The Principles and Applications of Decision Analysis, volume 2, chapter 37, pages 721-762. Strategic Decision Group, 1981.
4. Frank Jensen, Finn V. Jensen, and Sren L. Dittmer. From influence diagrams to junction trees. In Ramon Lopez de Mantaras and David Poole, editors, Proceedings of the Tenth Conference on Uncertainty in Artificial Intelligence, pages 367-373. Morgan Kaufmann Publishers, 1994.
5. Anders L. Madsen and Finn V. Jensen. Lazy evaluation of symmetric Bayesian decision problems. In Kathryn B. Laskey and Henri Prade, editors, Proceedings of the Fifthteenth Conference on Uncertainty in Artificial Intelligence. Morgan Kaufmann Publishers, 1999.
6. Thomas D. Nielsen and Finn V. Jensen. Welldefined decision scenarios. In Kathryn B. Laskey and Henri Prade, editors, Proceedings of the Fifthteenth Conference on Uncertainty in Artificial Intelligence. Morgan Kaufmann Publishers, 1999.
7. Thomas D. Nielsen and Finn V. Jensen. Welldefined decision scenarios. Technical Report R-01-5002, Department of Computer Science, Fredrik Bajers 7E, 9220 Aalborg, Denmark, 2001.
8. Dennis Nilsson and Finn V. Jensen. Probabilities of future decisions. In Information, Uncertainty and Fusion, pages 161-171. Kluwer Academic Publishers, 2000.
9. Ross D. Shachter. Bayes ball: The rational pastime (for determining irrelevance and requisite information in belief networks and influence diagrams). In Gregory F. Cooper and Seran Moral, editors, Proceedings of the Fourteenth Conference on Uncertainty in Artificial Intelligence, pages 480-487. Morgan Kaufmann Publishers, 1998.
10. Ross D. Shachter. Efficient value of information computation. In Kathryn B. Laskey and Henri Prade, editors, Proceedings of the Fifthteenth Conference on Uncertainty in Artificial Intelligence, pages 594-601. Morgan Kaufmann Publishers, 1999.
11. Ross D. Shachter. Evaluating influence diagrams. Operations Research Society of America, 34(6):79-90, February 1986.
12. Ross D. Shachter and Mark A. Peot. Decision making using probabilistic inference methods. In Didier Dubois, Michael P. Wellman, Bruce D'Ambrosio, and Phillipe Smets, editors, Proceedings of the Eighth Conference on Uncertainty in Artificial Intelligence, pages 276-283. Morgan Kaufmann Publishers, 1992.
13. Prakash P. Shenoy. Valuation-based systems for Bayesian decision analysis. Operations Research, 40(3):463-484, 1992.
14. Joseph. A. Tatman and Ross. D. Shachter. Dynamic programming and influence diagrams. IEEE Transactions on Systems, Man and Cybernetics, 20(2):365-379, March/April 1990.