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AAAI 2018

Rank Maximal Equal Contribution: A Probabilistic Social Choice Function

Conference Paper AAAI Technical Track: Game Theory and Economic Paradigms Artificial Intelligence

Abstract

When aggregating preferences of agents via voting, two desirable goals are to incentivize agents to participate in the voting process and then identify outcomes that are Pareto efficient. We consider participation as formalized by Brandl, Brandt, and Hofbauer (2015) based on the stochastic dominance (SD) relation. We formulate a new rule called RMEC (Rank Maximal Equal Contribution) that is polynomial-time computable, ex post efficient and satisfies the strongest notion of participation. It also satisfies many other desirable fairness properties. The rule suggests a general approach to achieving very strong participation, ex post efficiency and fairness.

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Context

Venue
AAAI Conference on Artificial Intelligence
Archive span
1980-2026
Indexed papers
28718
Paper id
436300848324531714
v2026.09.13