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Bayesian Rules of Updating

In: Probability, Dynamics and Causality

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  • Colin Howson

    (London School of Economics, Department of Philosophy)

Abstract

This paper discusses the Bayesian updating rules of ordinary and Jeffrey conditionalisation. Their justification has been a topic of interest for the last quarter century, and several strategies proposed. None has been accepted as conclusive, and it is argued here that this is for a good reason; for by extending the domain of the probability function to include propositions describing the agent’s present and future degrees of belief one can systematically generate a class of counterexamples to the rules. Dynamic Dutch Book and other arguments for them are examined critically. A concluding discussion attempts to put these results in perspective within the Bayesian approach.

Suggested Citation

  • Colin Howson, 1997. "Bayesian Rules of Updating," Springer Books, in: Domenico Costantini & Maria Carla Galavotti (ed.), Probability, Dynamics and Causality, pages 55-68, Springer.
    • Handle: RePEc:spr:sprchp:978-94-011-5712-4_4
    DOI: 10.1007/978-94-011-5712-4_4
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