On Shannon-Jaynes Entropy and Fisher Information

Abstract

The fundamentals of the Maximum Entropy principle as a rule for assigning and updating probabilities are revisited. The Shannon-Jaynes relative entropy is vindicated as the optimal criterion for use with an updating rule. A constructive rule is justified which assigns the probabilities least sensitive to coarse-graining. The implications of these developments for interpreting physics laws as rules of inference upon incomplete information are briefly discussed.