Abstract
Probabilistic logic leads to intractable linear programs when there are too many ‘possible worlds’. Practical inference problems, however, often have structural regularity which can trim linear constraint systems. This paper emphasizes modus ponens with consequents of unknown probability. Contingency tables provide linear constraints for the priors and motivate useful revision assumptions.
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Literature Cited
Jeffrey, R., The Logic of Decisions, Chicago: U. Chicago, 1983.
Kane, T., Maximum entropy in Nilsson's probabilistic logic, Proc. IJCAI, 452–457, 1989.
Nilsson, N.J., Probabilistic logic, Artif. Intell. 28, 71–87, 1986.
Snow, P., Improved posterior probability estimates from prior and conditional linear constraint systems, IEEE Trans. Syst. Man & Cybern. 21, 464–469, 1991a.
-, Compressed constraints in probabilistic logic and their revision, in B.D. D'Ambrosio, P. Smets, and P.P. Bonissone (eds.), Uncertainty in Artificial Intelligence, San Mateo, CA: Morgan Kaufmann, 1991b.
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© 1991 Springer-Verlag Berlin Heidelberg
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Snow, P. (1991). Restraining the proliferation of worlds in probabilistic logic entailments. In: Kruse, R., Siegel, P. (eds) Symbolic and Quantitative Approaches to Uncertainty. ECSQARU 1991. Lecture Notes in Computer Science, vol 548. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-54659-6_108
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DOI: https://doi.org/10.1007/3-540-54659-6_108
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