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A Kripke-Lewis semantics for belief update and belief revision

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  • Giacomo Bonanno

    (Department of Economics, University of California Davis)

Abstract

We provide a new characterization of both belief update and belief revision in terms of a Kripke-Lewis semantics. We consider frames consisting of a set of states, a Kripke belief relation and a Lewis selection function. Adding a valuation to a frame yields a model. Given a model and a state, we identify the initial belief set K with the set of formulas that are believed at that state and we identify either the updated belief set or the revised belief set, prompted by the input represented by formula A, as the set of formulas that are the consequent of conditionals that (1) are believed at that state and (2) have A as antecedent. We show that this class of models characterizes both the Katsuno-Mendelzon (KM) belief update functions and the AGM belief revision functions, in the following sense: (1) each model gives rise to a partial belief function that can be completed into a full KM/AGM update/revision function, and (2) for every KM/AGM update/revision function there is a model whose associated belief function coincides with it. The difference between update and revision can be reduced to two semantic properties that appear in a stronger form in revision relative to update, thus confirming the finding by Peppas et al. (1996) that, "for a fixed theory K, revising K is much the same as updating K"

Suggested Citation

  • Giacomo Bonanno, 2023. "A Kripke-Lewis semantics for belief update and belief revision," Working Papers 358, University of California, Davis, Department of Economics.
  • Handle: RePEc:cda:wpaper:358
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    File URL: https://repec.dss.ucdavis.edu/files/P3JCTSiRXZdRk6XgowAWpUmL/UpdRev.pdf
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    More about this item

    Keywords

    belief revision; belief update; indicative conditional; subjunctive conditional; belief relation; selection function; supposition; information.;
    All these keywords.

    JEL classification:

    • C0 - Mathematical and Quantitative Methods - - General

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