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Rajarshi GHOSH - ESSEC

"Quadratically Normalized Utilitarian Voting"
Joint work with Prof. Marcus Pivato

Abstract :

Most incentive compatible mechanisms that achieve utilitarian optimality require voters to express the intensity of their preferences using money (e.g. by bidding or buying votes). Furthermore, they assume that the utilities of the voters are quasi-linear in money. Moreover, mechanisms in the current literature that use an artificial currency can only be applied to multiple simultaneous binary decisions. We propose a new mechanism named "Quadratically Normalized Utilitarian Voting" which does not use money to buy votes, does not assume quasi-linearity of the voters’ utilities, and can be applied to single propositions with two or more alternatives. We show that voters vote in proportion to their true utility for an alternative in all Nash Equilibria and that the mechanism maximizes a weighted utilitarian social welfare function at each such equilibrium.

avril 2023 :

mars 2023 | mai 2023