Belief Expansion, Contextual Fit and the Reliability of Information Sources

In Varol Akman (ed.), Modeling and Using Context (Lecture Notes in Artificial Intelligence 2116). Springer. pp. 421-424 (2001)
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Abstract

We develop a probabilistic criterion for belief expansion that is sensitive to the degree of contextual fit of the new information to our belief set as well as to the reliability of our information source. We contrast our approach with the success postulate in AGM-style belief revision and show how the idealizations in our approach can be relaxed by invoking Bayesian-Network models

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Author Profiles

Stephan Hartmann
Ludwig Maximilians Universität, München
Luc Bovens
University of North Carolina, Chapel Hill

Citations of this work

Truth-conditional pragmatics: an overview.Francois Recanati - 2008 - In Richmond Thomason, Paolo Bouquet & Luciano Serafini (eds.), Perspectives on Context. CSLI Stanford. pp. 171-188.

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