Synthese 187 (1):147-178 (2012)

Authors
Anubav Vasudevan
Columbia University
Haim Gaifman
Columbia University
Abstract
The technique of minimizing information (infomin) has been commonly employed as a general method for both choosing and updating a subjective probability function. We argue that, in a wide class of cases, the use of infomin methods fails to cohere with our standard conception of rational degrees of belief. We introduce the notion of a deceptive updating method and argue that non-deceptiveness is a necessary condition for rational coherence. Infomin has been criticized on the grounds that there are no higher order probabilities that ‘support’ it, but the appeal to higher order probabilities is a substantial assumption that some might reject. Our elementary arguments from deceptiveness do not rely on this assumption. While deceptiveness implies lack of higher order support, the converse does not, in general, hold, which indicates that deceptiveness is a more objectionable property. We offer a new proof of the claim that infomin updating of any strictly-positive prior with respect to conditional-probability constraints is deceptive. In the case of expected-value constraints, infomin updating of the uniform prior is deceptive for some random variables but not for others. We establish both a necessary condition and a sufficient condition (which extends the scope of the phenomenon beyond cases previously considered) for deceptiveness in this setting. Along the way, we clarify the relation which obtains between the strong notion of higher order support, in which the higher order probability is defined over the full space of first order probabilities, and the apparently weaker notion, in which it is defined over some smaller parameter space. We show that under certain natural assumptions, the two are equivalent. Finally, we offer an interpretation of Jaynes, according to which his own appeal to infomin methods avoids the incoherencies discussed in this paper.
Keywords Updating proabilities  Minimal information  Higher order probabilities  Maximum entropy  Cross entropy  Jaynes
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DOI 10.1007/s11229-011-0028-0
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References found in this work BETA

The Foundations of Statistics.Leonard J. Savage - 1954 - Wiley Publications in Statistics.
The Logic of Decision.Richard C. Jeffrey - 1965 - New York, NY, USA: University of Chicago Press.
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Probabilities Over Rich Languages, Testing and Randomness.Haim Gaifman & Marc Snir - 1982 - Journal of Symbolic Logic 47 (3):495-548.

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Citations of this work BETA

Entropy and Insufficient Reason: A Note on the Judy Benjamin Problem.Anubav Vasudevan - 2020 - British Journal for the Philosophy of Science 71 (3):1113-1141.
Speed-Optimal Induction and Dynamic Coherence.Michael Nielsen & Eric Wofsey - forthcoming - British Journal for the Philosophy of Science:axz030.

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