Abstract
By probabilistic logic I mean a normative theory of belief that explains how a body of evidence affects one's degree of belief in a possible hypothesis. A new axiomatization of such a theory is presented which avoids a finite additivity axiom, yet which retains many useful inference rules. Many of the examples of this theory--its models do not use numerical probabilities. Put another way, this article gives sharper answers to the two questions: 1.What kinds of sets can used as the range of a probability function? 2.Under what conditions is the range set of a probability function isomorphic to the set of real numbers in the interval 10,1/ with the usual arithmetical operations?
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