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Imprecision in decision analysis is modeled using fuzzy-set theory. Fuzziness on the probabilities and utilities used in a decision analysis implies fuzziness on the outputs; a method is suggested for calculating imprecise, though informative, statements about the attractiveness of the different options in a decision tree, which depends on the imprecision of the inputs. A general discussion of the advantages and disadvantages of the approach is given.
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Stored only when both papers are in the corpus — 253 citations exist upstream.
Papers that cite the same references — the relational fallback while embeddings are still backfilling.
Imported from OpenAlex (CC0) — nothing here is generated.