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Modeling Partially Reliable Information Sources: A General Approach Based on Dempster-Shafer Theory

Stephan Hartmann & Rolf Haenni

Information Fusion 7:361-379 (2006)

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Bayesian Epistemology.Stephan Hartmann & Jan Sprenger - 2010 - In Sven Bernecker & Duncan Pritchard (eds.), The Routledge Companion to Epistemology. New York: Routledge. pp. 609-620.details Bayesian epistemology addresses epistemological problems with the help of the mathematical theory of probability. It turns out that the probability calculus is especially suited to represent degrees of belief (credences) and to deal with questions of belief change, confirmation, evidence, justification, and coherence. Compared to the informal discussions in traditional epistemology, Bayesian epis- temology allows for a more precise and fine-grained analysis which takes the gradual aspects of these central epistemological notions into account. Bayesian epistemology therefore complements traditional epistemology; it (...) Download Export citation Bookmark 43 citations
Three conceptions of explaining how possibly—and one reductive account.Johannes Persson - 2011 - In Henk W. De Regt, Stephan Hartmann & Samir Okasha (eds.), EPSA Philosophy of Science: Amsterdam 2009. Springer. pp. 275--286.details Philosophers of science have often favoured reductive approaches to how-possibly explanation. This article identifies three alternative conceptions making how-possibly explanation an interesting phenomenon in its own right. The first variety approaches “how possibly X?” by showing that X is not epistemically impossible. This can sometimes be achieved by removing misunderstandings concerning the implications of one’s current belief system but involves characteristically a modification of this belief system so that acceptance of X does not result in contradiction. The second variety offers (...) Download Export citation Bookmark 8 citations
Probabilistic Logics and Probabilistic Networks.Rolf Haenni, Jan-Willem Romeijn, Gregory Wheeler & Jon Williamson - 2010 - Dordrecht, Netherland: Synthese Library. Edited by Gregory Wheeler, Rolf Haenni, Jan-Willem Romeijn & and Jon Williamson.details Additionally, the text shows how to develop computationally feasible methods to mesh with this framework. Download Export citation Bookmark 24 citations
Learning juror competence: a generalized Condorcet Jury Theorem.Jan-Willem Romeijn & David Atkinson - 2011 - Politics, Philosophy and Economics 10 (3):237-262.details This article presents a generalization of the Condorcet Jury Theorem. All results to date assume a fixed value for the competence of jurors, or alternatively, a fixed probability distribution over the possible competences of jurors. In this article, we develop the idea that we can learn the competence of the jurors by the jury vote. We assume a uniform prior probability assignment over the competence parameter, and we adapt this assignment in the light of the jury vote. We then compute (...) Download Export citation Bookmark 6 citations
Meta-analysis as Judgment Aggregation.Berna Kilinc - 2011 - In Henk W. De Regt, Stephan Hartmann & Samir Okasha (eds.), EPSA Philosophy of Science: Amsterdam 2009. Springer. pp. 123--135.details My goal in this paper is to see the extent to which judgment aggregation methods subsume meta-analytic ones. To this end, I derive a generalized version of the classical Condorcet Jury Theorem, the aggregative implications of which have been widely exploited in the area of rational choice theory, but not yet in philosophy of science. I contend that the generalized CJT that I prove below is useful for modelling at least some meta-analytic procedures. Download Export citation Bookmark

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