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Theoretical Computer Science
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A formula for incorporating weights into scoring rules

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Abstract

A "scoring rule" is an assignment of a value to every tuple (of varying sizes). This paper is concerned with the issue of how to modify a scoring rule to apply to the case where weights are assigned to the importance of each argument. We give an explicit formula for incorporating weights that can be applied no matter what the underlying scoring rule is. The formula is surprisingly simple, in that it involves far fewer terms than one might have guessed. It has three further desirable properties. The first desirable property is that when all of the weights are equal, then the result is obtained by simply using the underlying scoring rule. Intuitively, this says that when all of the weights are equal, then this is the same as considering the unweighted case. The second desirable property is that if a particular argument has zero weight, then that argument can be dropped without affecting the value of the result. The third desirable property is that the value of the result is a continuous function of the weights. We show that if these three desirable properties hold, then under one additional assumption (a type of local linearity), our formula gives the unique possible answer. © 2000 Elsevier Science B.V. All rights reserved.

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Theoretical Computer Science

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