A Unified Characterization of Belief Revision Rules
Franz Dietrich, Christian List, Richard A. Bradley · Munich Personal RePEc Archive (Ludwig Maximilian University of Munich) · 2014
This paper characterizes several belief-revision rules in a unified framework: Bayesian revision upon learning some event, Jeffrey revision upon learning new probabilities of some events, Adams revision upon learning some new conditional probabilities, and 'dual-Jeffrey' revision upon learning a new conditional probability function. Despite their differences, these revision rules can be characterized in terms of the same two 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. So, the four revision rules apply the same principles, albeit to different learnt inputs. To illustrate that there is room for non-Bayesian belief revision in economic theory, we also sketch a simple decision-theoretic application.