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A state-of-the-art guide to formal epistemology
Probability is a hot topic in philosophy
Written for non-specialists, including advanced students
Original, lively, clear, and up-to-date
Truly interdisciplinary - relevant to philosophy, cognitive science, economics, and jurisprudence
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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.



Table of Contents
Introduction
1: Information
2: Coherence
3: Reliability
4: Confirmation
5: Testimony
Epilogue
Appendix