# Defeasible Conditionalization

*Journal of Philosophical Logic*43 (2-3):283-302 (2014)

**Abstract**

The applicability of Bayesian conditionalization in setting one’s posterior probability for a proposition, α, is limited to cases where the value of a corresponding prior probability, PPRI(α|∧E), is available, where ∧E represents one’s complete body of evidence. In order to extend probability updating to cases where the prior probabilities needed for Bayesian conditionalization are unavailable, I introduce an inference schema, defeasible conditionalization, which allows one to update one’s personal probability in a proposition by conditioning on a proposition that represents a proper subset of one’s complete body of evidence. While defeasible conditionalization has wider applicability than standard Bayesian conditionalization (since it may be used when the value of a relevant prior probability, PPRI(α|∧E), is unavailable), there are circumstances under which some instances of defeasible conditionalization are unreasonable. To address this difficulty, I outline the conditions under which instances of defeasible conditionalization are defeated. To conclude the article, I suggest that the prescriptions of direct inference and statistical induction can be encoded within the proposed system of probability updating, by the selection of intuitively reasonable prior probabilities

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References found in this work BETA

Laws and Symmetry.van Fraassen, Bas C.

Betting on Theories.Maher, Patrick

The Logic of Decision.Jeffrey, Richard

Logical Foundations of Probability.Carnap, Rudolf

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Citations of this work BETA

Admissibility Troubles for Bayesian Direct Inference Principles.Wallmann, Christian & Hawthorne, James

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