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Jaynes's maximum entropy prescription and probability theory

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Abstract

Jaynes's prescription of maximizing the information-theoretic entropy is applied in a special situation to determine a certain set of posterior probabilities (when evidence fixing the expected value of a dynamical variable is given) and also the corresponding set of prior probabilities (when this evidence is not given). It is shown that the resulting values of these probabilities are inconsistent with the principles of probability theory. Three possible ways of avoiding this inconsistency are briefly discussed.

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Authors and Affiliations

  1. Department of Philosophy, State University of New York, Oswego, New York

    Kenneth Friedman

  2. Departments of Philosophy and Physics, Boston University, Boston, Massachusetts

    Abner Shimony

Authors
  1. Kenneth Friedman
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  2. Abner Shimony
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Friedman, K., Shimony, A. Jaynes's maximum entropy prescription and probability theory. J Stat Phys 3, 381–384 (1971). https://doi.org/10.1007/BF01008275

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  • DOI: https://doi.org/10.1007/BF01008275

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