Dempster's rule as seen by little colored balls

Computational Intelligence

Volumn 28, Issue 4, 2012, Pages 453-474

  Jøsang, Audun ^a   Pope, Simon ^b  

^a UNIVERSITY OF OSLO   (Norway)

^b MICROSOFT   (United States)

Author keywords

averaging operator; belief theory; cumulative operator; fusion; subjective logic

Indexed keywords

AVERAGING OPERATORS; BELIEF FUNCTION; BELIEF FUSION; BELIEF THEORY; COLORED BALLS; CUMULATIVE OPERATOR; DEMPSTER'S RULE; DEMPSTER'S RULE OF COMBINATION; FREQUENTIST; FUNDAMENTAL PRINCIPLES; FUSION OPERATOR; STOCHASTIC CONSTRAINTS; SUBJECTIVE LOGIC;

ARTIFICIAL INTELLIGENCE; COMPUTATIONAL METHODS; FUSION REACTIONS;

UNCERTAINTY ANALYSIS;

EID: 84868142548     PISSN: 08247935     EISSN: 14678640     Source Type: Journal    
DOI: 10.1111/j.1467-8640.2012.00421.x     Document Type: Article

References (28)

1. Daniel, M., 2000. Associativity in combination of belief functions. In Proceedings of 5th Workshop on Uncertainty Processing.- Praha, Edicni oddeleni VSE 2000, Springer, pp. 41-54.
2. De Finetti, B., 1974a. The true subjective probability problem. In The Concept of Probability in Psychological Experiments. Edited by, C.-A. Staël von Holstein,. D.Reidel Publishing Company, Dordrecht, Holland, pp. 15-23.
3. De Finetti, B., 1974b. The value of studying subjective evaluations of probability. In The Concept of Probability in Psychological Experiments. Edited by, C.-A. Staël von Holstein,. D.Reidel Publishing Company: Dordrecht, Holland, pp. 1-14.
4. Destercke, S., and, D. Dubois,. 2010. Idempotent merging of belief functions: Extending the minimum rule of possibility theory. In Workshop on the Theory on Belief Functions (WTBF 2010), Edited by, T. Denåx,.
5. Dubois, D., and, H. Prade,. 1986. On the unicity of Dempster's rule of combination. International Journal of Intelligent Systems, 1: 133-142.
6. Dubois, D., and, H. Prade,. 1988. Representation and combination of uncertainty with belief functions and possibility measures. Computational Intelligence, 4: 244-264.
7. Haenni, R., 2003. Ignoring Ignorance Is Ignorant. Working paper of the Philosophy, Probability, and Modeling Research Group, University of Konstanz.
8. Haenni, R., 2005. Shedding new light on Zadeh's criticism of Dempster's rule of combination. In Proceedings of Information Fusion.
9. Hájek, P., and, J. J. Valdés,. 1991. Generalized algebraic foundations of uncertainty processing in rule-based expert systems (dempsteroids). Computers and Artificial Intelligence, 10: 294-294.
10. Hájek, P., T. Havránek, and, R. Jiroušek,. 1992. Uncertain Information Processing in Expert Systems. CRC Press: Boca Raton, FL.
11. Halpern, J. Y., and, R. Fagin,. 1992. Two views of belief: Belief as generalised probability and belief as evidence. Artificial Intelligence, 54: 275-275.
12. Jøsang, A., 1997. Artificial reasoning with subjective logic. In Proceedings of the 2nd Australian Workshop on Commonsense Reasoning. Edited by, A. Nayak, and, M. Pagnucco, Australian Computer Society, Perth.
13. Jøsang, A., 2002. The consensus operator for combining beliefs. Artificial Intelligence Journal, 142 (1-2): 157-157.
14. Jøsang, A., 2007. Probabilistic logic under uncertainty. In The Proceedings of Computing: The Australian Theory Symposium (CATS2007), CRPIT Vol. 65, Ballarat, Australia.
15. Jøsang, A., and, Hankin, R., 2012. Interpretation and Fusion of Hyper Opinions in Subjective Logic. In Proceedings of the 15th International Conference on Information Fusion (FUSION 2012).
16. Jøsang, A., 2011. Multi-Agent Preference Combination using Subjective Logic. In International Workshop on Preferences and Soft Constraints (Soft'11), Perugia, Italy.
17. Jøsang, A., and, Z. Elouedi,. 2007. Interpreting belief functions as Dirichlet distributions. In The Proceedings of the 9th European Conference on Symbolic and Quantitative Approaches to Reasoning with Uncertainty (ECSQARU), Hammamet, Tunisia.
18. Jøsang, A., and, D. McAnally,. 2004. Multiplication and comultiplication of beliefs. International Journal of Approximate Reasoning, 38 (1): 19-51.
19. Jøsang, A., J. Diaz, and, M. Rifqi,. 2010. Cumulative and averaging fusion of beliefs. Information Fusion, 11 (2): 192-192. doi:10.1016/j.inffus.2009.05.005.
20. Klawonn, F., and, E. Schwecke,. 1992. On the axiomatic justification of Dempster's rule of combination. International Journal of Intelligent Systems, 7: 469-469.
21. Kohlas, J., and, P. Monney,. 1995. A Mathematical Theory of Hints. An Approach to Dempster-Shafer Theory of Evidence, Volume 425 of Lecture Notes in Economics and Mathematical Systems, Springer-Verlag.
22. Lefevre, E., O. Colot, and, P. Vannoorenberghe,. 2002. Belief functions combination and conflict management. Information Fusion, 3 (2): 149-149.
23. Murphy, C. K., 2000. Combining belief functions when evidence conflicts. Decision Support Systems, 29: 1-9.
24. Shafer, G., 1976. A Mathematical Theory of Evidence. Princeton University Press: Princeton, NJ.
25. Smets, P., 1990. The combination of evidence in the transferable belief model. IEEE Transactions on Pattern Analysis and Machine Intelligence, 12 (5): 447-447.
26. Voorbraak, F., 1991. On the justification of Dempster's rule of combinations. Artificial Intelligence, 48: 171-171.
27. Yager, R., 1987. On the Dempster-Shafer framework and new combination rules. Information Sciences, 41: 93-137.
28. Zadeh, L., 1984. Review of Shafer's mathematical theory of evidence. AI Magazine, 5: 81-83.