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.
Cite
CITATION STYLE
Bovens, L., & Hartmann, S. (2001). Belief expansion, contextual fit, and the reliability of information sources. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 2116, pp. 421–424). Springer Verlag. https://doi.org/10.1007/3-540-44607-9_34
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