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Robust Winner Determination in Positional Scoring Rules with Uncertain Weights

Paolo Viappiani 1
1 DECISION
LIP6
Abstract : Scoring rules constitute a particularly popular technique for aggregating a set of rank-ings. However, setting the weights associated to rank positions is a crucial task, as different instantiations of the weights can often lead to different winners. In this work we adopt minimax regret as a robust criterion for determining the winner in the presence of uncertainty over the weights. Focusing on two general settings (non-increasing weights and convex sequences of non-increasing weights) we provide a characterization of the minimax regret rule in terms of cumulative ranks, allowing a quick computation of the winner. We then analyze the properties of using minimax regret as a social choice function. Finally we provide some test cases of rank aggregation using the proposed method.
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https://hal.sorbonne-universite.fr/hal-02373399
Contributor : Paolo Viappiani <>
Submitted on : Wednesday, November 20, 2019 - 11:44:11 PM
Last modification on : Monday, July 20, 2020 - 1:27:43 PM

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Paolo Viappiani. Robust Winner Determination in Positional Scoring Rules with Uncertain Weights. Theory and Decision, Springer Verlag, 2020, 88 (3), pp.323-367. ⟨10.1007/s11238-019-09734-3⟩. ⟨hal-02373399⟩

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