Belief Expansion, Contextual Fit, and the Reliability of Information Sources

Bovens, Luc und Hartmann, Stephan (2001): Belief Expansion, Contextual Fit, and the Reliability of Information Sources. In: Akman, Varol; Bouquet, Paolo; Thomason, Richmond und Young, Roger (Hrsg.): Modeling and Using Context. Lecture Notes in Artificial Intelligence, Bd. 2116. Berlin: Springer-Verlag. S. 421-424

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.

• Dokumententyp: Buchbeitrag
• Publikationsform: Postprint
• Fakultät: Philosophie, Wissenschaftstheorie und Religionswissenschaft > Munich Center for Mathematical Philosophy (MCMP) ; Philosophie, Wissenschaftstheorie und Religionswissenschaft > Munich Center for Mathematical Philosophy (MCMP) > Philosophy of Science
• Themengebiete: 100 Philosophie und Psychologie > 100 Philosophie
• ISBN: 978-3-540-42379-9
• Ort: Berlin
• Sprache: Englisch