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Two Endorsement-based Approaches to Reasoning About Uncertainty

Abstract

Two approaches to reasoning about uncertainty are discussed. A parallel certainty inference model superimposes reasoning about the credibility of inferences on a deductive framework. A second approach identifies and implements representativeness as the general determinant of credibility in classification tasks. These approaches are steps in the evolution of endorsement-based reasoning, a view of uncertainty in terms of structured objects that represent characteristics of evidence

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