David Bourget (Western Ontario)
David Chalmers (ANU, NYU)
Rafael De Clercq
Jack Alan Reynolds
Learn more about PhilPapers
OUP Oxford (2004)
Probabilistic models have much to offer to philosophy. We continually receive information from a variety of sources: from our senses, from witnesses, from scientific instruments. When considering whether we should believe this information, we assess whether the sources are independent, how reliable they are, and how plausible and coherent the information is. Bovens and Hartmann provide a systematic Bayesian account of these features of reasoning. Simple Bayesian Networks allow us to model alternative assumptions about the nature of the information sources. Measurement of the coherence of information is a controversial matter: arguably, the more coherent a set of information is, the more confident we may be that its content is true, other things being equal. The authors offer a new treatment of coherence which respects this claim and shows its relevance to scientific theory choice. Bovens and Hartmann apply this methodology to a wide range of much discussed issues regarding evidence, testimony, scientific theories, and voting. Bayesian Epistemology is an essential tool for anyone working on probabilistic methods in philosophy, and has broad implications for many other disciplines.
|Keywords||No keywords specified (fix it)|
|Categories||categorize this paper)|
|Buy the book||$89.89 used (10% off) $94.00 new (6% off) $99.00 direct from Amazon Amazon page|
Setup an account with your affiliations in order to access resources via your University's proxy server
Configure custom proxy (use this if your affiliation does not provide a proxy)
|Through your library|
References found in this work BETA
No references found.
Citations of this work BETA
Joshua Shepherd & James Justus (2015). X-Phi and Carnapian Explication. Erkenntnis 80 (2):381-402.
Adam J. L. Harris, Ulrike Hahn, Jens K. Madsen & Anne S. Hsu (2015). The Appeal to Expert Opinion: Quantitative Support for a Bayesian Network Approach. Cognitive Science 39 (7).
Mike Oaksford & Nick Chater (2009). Précis of Bayesian Rationality: The Probabilistic Approach to Human Reasoning. Behavioral and Brain Sciences 32 (1):69-84.
Jakob Hohwy (2013). Delusions, Illusions and Inference Under Uncertainty. Mind and Language 28 (1):57-71.
Similar books and articles
Wouter Meijs (2007). A Corrective to Bovens and Hartmann's Measure of Coherence. Philosophical Studies 133 (2):151 - 180.
W. Meijs (2007). A Corrective to Bovens and Hartmann's Measure of Coherence. Philosophical Studies 133 (2):151 - 180.
Stephan Hartmann & Luc Bovens (2002). Bayesian Networks and the Problem of Unreliable Instruments. Philosophy of Science 69 (1):29-72.
Toinoji Shogenji (2006). Luc Bovens and Stephan Hartmann, Bayesian Epistemology Oxford University Press, 2004, Pp. IX+ 159.Isbn 0-19-926975-0 (Hardback), Isbn 0-19-927040-6 (Paperback). [REVIEW] Theoria 72 (2):166-171.
Stephan Hartmann & Jan Sprenger (forthcoming). Bayesian Epistemology. In Duncan Pritchard & Sven Bernecker (eds.), Routledge Companion to Epistemology. Routledge
Alan Hájek & Stephan Hartmann (2010). Bayesian Epistemology. In J. Dancy et al (ed.), A Companion to Epistemology. Blackwell
Stephan Hartmann & Luc Bovens (2002). Bayesian Networks in Philosophy. In Benedikt Löwe, Wolfgang Malzkorn & Thoralf Räsch (eds.), Foundations of the Formal Sciences II: Applications of Mathematical Logic in Philosophy and Linguistics. Kluwer 39-46.
Luc Bovens & Stephan Hartmann (2003). Bayesian Epistemology. Oxford: Oxford University Press.
Added to index2009-01-28
Total downloads35 ( #91,921 of 1,725,161 )
Recent downloads (6 months)1 ( #349,161 of 1,725,161 )
How can I increase my downloads?