Bayesian, Jeffrey and Field conditionals are compared and it is shown why the last two cannot be reduced to the first. Maximum relative entropy is used in two kinds of justification of the Field conditional and the dispensability of entropy principles in general is discussed.

Recent years have seen a renewed interest in the philosophical study of information. In this paper a two-part analysis of information gain—objective and subjective—in the context of doxastic change is presented and discussed. Objective information gain is analyzed in terms of doxastic movement towards true belief, while subjective information gain is analyzed as an agent’s expectation value of her objective information gain for a given doxastic change. The resulting expression for subjective information gain turns out to be a familiar one (...) with well-known formal properties: the Kullback–Leibler divergence. The two notions of information are discussed and the suggested measure of subjective information gain is then compared with the widely held view that information gain equals uncertainty reduction. (shrink)

The lore is that standard information theory provides an analysis of information quantity, but not of information content. I argue this lore is incorrect, and there is an adequate informational semantics latent in standard theory. The roots of this notion of content can be traced to the secret parallel development of an information theory equivalent to Shannon’s by Turing at Bletchley Park, and it has been suggested independently in recent work by Skyrms and Bullinaria and Levy. This paper explicitly articulates (...) the semantics latent in information theory and defends it as an adequate theory of information content, or natural meaning. I argue that this theory suggests a new perspective on the classic misrepresentation worry for correlation-based semantics. (shrink)