Uncertainty in Artificial Intelligence
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Probabilistic Assumption-Based Reasoning
Jurg Kohlas, Paul-Andre Monney
The classical propositional assumption-based model is extended to incorporate probabilities for the assumptions. Then it is placed into the framework of evidence theory. Several authors like Laskey, Lehner (1989) and Provan (1990) already proposed a similar point of view, but the first paper is not as much concerned with mathematical foundations, and Provan's paper develops into a different direction. Here we thoroughly develop and present the mathematical foundations of this theory, together with computational methods adapted from Reiter, De Kleer (1987) and Inoue (1992). Finally, recently proposed techniques for computing degrees of support are presented.
Pages: 485-491
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PDF Link: /papers/93/p485-kohlas.pdf
AUTHOR = "Jurg Kohlas and Paul-Andre Monney",
TITLE = "Probabilistic Assumption-Based Reasoning",
BOOKTITLE = "Proceedings of the Ninth Conference Annual Conference on Uncertainty in Artificial Intelligence (UAI-93)",
PUBLISHER = "Morgan Kaufmann",
ADDRESS = "San Francisco, CA",
YEAR = "1993",
PAGES = "485--491"

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