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Uncertain evidence and artificial analysis. (English) Zbl 0655.62110
Summary: A belief function measure of uncertainty, associated with a network based knowledge structure, effectively defines an artificial analyst (e.g., an expert system) capable of making uncertain judgments. In practice, a belief function is typically constructed by combining independent components developed on local areas of the network from inputs such as accepted causal theories, probabilistic judgments by experts, or empirical sample data. Representation of the network in a special form called a ‘tree of cliques’ leads to a locally controlled algorithm that propagates locally defined beliefs through the tree, and fuses the resulting beliefs at the nodes, in such a way as to simultaneously compute marginal beliefs over all nodes of the tree. The paper develops a simple hypothetical example from the field of reliability to illustrate these ideas.

MSC:
62P99 Applications of statistics
62A01 Foundations and philosophical topics in statistics
62N99 Survival analysis and censored data
90B25 Reliability, availability, maintenance, inspection in operations research
68T99 Artificial intelligence
94C99 Circuits, networks
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