Uncertainty in Artificial Intelligence
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Probabilistic Belief Change: Expansion, Conditioning and Constraining
Frans Voorbraak
Abstract:
The AGM theory of belief revision has become an important paradigm for investigating rational belief changes. Unfortunately, researchers working in this paradigm have restricted much of their attention to rather simple representations of belief states, namely logically closed sets of propositional sentences. In our opinion, this has resulted in a too abstract categorisation of belief change operations: expansion, revision, or contraction. Occasionally, in the AGM paradigm, also probabilistic belief changes have been considered, and it is widely accepted that the probabilistic version of expansion is conditioning. However, we argue that it may be more correct to view conditioning and expansion as two essentially different kinds of belief change, and that what we call constraining is a better candidate for being considered probabilistic expansion.
Keywords: probabilistic belief change, expansion, conditioning, constraining , sets of probabil
Pages: 655-662
PS Link: http://turing.wins.uva.nl/~fransv/articles/UAI99.ps
PDF Link: /papers/99/p655-voorbraak.pdf
BibTex:
@INPROCEEDINGS{Voorbraak99,
AUTHOR = "Frans Voorbraak ",
TITLE = "Probabilistic Belief Change: Expansion, Conditioning and Constraining",
BOOKTITLE = "Proceedings of the Fifteenth Conference Annual Conference on Uncertainty in Artificial Intelligence (UAI-99)",
PUBLISHER = "Morgan Kaufmann",
ADDRESS = "San Francisco, CA",
YEAR = "1999",
PAGES = "655--662"
}


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