Belief revision generalized: A joint characterization of Bayes' and Je¤rey's rules

Franz Dietrich, Christian List and Richard Bradley
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Christian List: LSE - London School of Economics and Political Science
Richard Bradley: LSE - London School of Economics and Political Science

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Abstract: We present a general framework for representing belief-revision rules and use it to characterize Bayes' rule as a classical example and Jeffrey's rule as a non-classical one. In Je¤rey's rule, the input to a belief revision is not simply the information that some event has occurred, as in Bayes' rule, but a new assignment of probabilities to some events. Despite their differences, Bayes' and Je¤rey's rules can be characterized in terms of the same axioms: responsiveness, which requires that revised beliefs incorporate what has been learnt, and conservativeness, which requires that beliefs on which the learnt input is 'silent' do not change. To illustrate the use of non-Bayesian belief revision in economic theory, we sketch a simple decision-theoretic application.

Keywords: fine-grained versus coarse-grained beliefs; axio-matic foundations; Belief revision; subjective probability; Bayes's rule; Je¤rey's rule; unawareness (search for similar items in EconPapers)
Date: 2016
Note: View the original document on HAL open archive server: https://shs.hal.science/halshs-01249635v1
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Published in Journal of Economic Theory, 2016, 162, pp.352-371

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Journal Article: Belief revision generalized: A joint characterization of Bayes' and Jeffrey's rules (2016)
Working Paper: Belief revision generalized: A joint characterization of Bayes' and Je¤rey's rules (2016)
Working Paper: Belief revision generalized: A joint characterization of Bayes' and Je¤rey's rules (2016)
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