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The paper considers a discrete stochastic multicrite- ria problem. This problem can be defined by a finite set of actions A, a set of attributes X and a set of evaluations E. It is assumed that the performance probability distributions for each action on each at- tribute are known. A new procedure for such a problem is proposed. It is based on two concepts: stochastic dominance and interactive approach. Stochastic dominance is employed for comparing evalua- tions of actions with respect to attributes. The STEM methodology is employed in the dialogue procedure between decision maker and decision model. In each step a candidate action ai is generated. The decision maker examines evaluations of ai with respect to attributes and selects the one that satisfies him/her. Then the decision maker defines the limit of concessions, which can be made on average eval- uations with respect to this attribute. The procedure continues until a satisfactory action is found.
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Stored only when both papers are in the corpus — 27 citations exist upstream.
Papers that cite the same references — the relational fallback while embeddings are still backfilling.
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