Readings in nonmonotonic reasoning
Readings in nonmonotonic reasoning
Artificial Intelligence
Advances in the Dempster-Shafer theory of evidence
Advances in the Dempster-Shafer theory of evidence
Representation of evidence by hints
Advances in the Dempster-Shafer theory of evidence
Uncertainty Models for Knowledge-Based Systems; A Unified Approach to the Measurement of Uncertainty
Uncertainty Models for Knowledge-Based Systems; A Unified Approach to the Measurement of Uncertainty
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The Dempster–Shafer belief structure provides a representation of a variable in which our knowledge of its probability distribution is imprecise. Here compatibility relations, which encode relationships between variables, enable inference about a consequent variable using knowledge about the input variable. Here we extend the capability of these compatibility relations to enable the representation of nonmonotonic relations, such as default rules. This allows situations in which an increase in information about the input variable can result in a decrease in information about the secondary variable. We show what are the conditions required of a compatibility relation to lead to monotonic and nonmonotonic inferences. We provide some examples of nonmonotonic relations.