Rank Maximal Equal Contribution: A Probabilistic Social Choice Function

Authors

  • Haris Aziz Data61, CSIRO and University of New South Wales
  • Pang Luo Data61, CSIRO and University of New South Wales
  • Christine Rizkallah University of Pennsylvania

DOI:

https://doi.org/10.1609/aaai.v32i1.11448

Keywords:

algorithms, game theory, social choice theory, probabilistic social choice, voting mechanisms, random serial dictatorship, ex post efficient, participation, fairness

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.

AAAI 2018 Proceedings Cover

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Published

2018-04-25

How to Cite

Aziz, H., Luo, P., & Rizkallah, C. (2018). Rank Maximal Equal Contribution: A Probabilistic Social Choice Function. Proceedings of the AAAI Conference on Artificial Intelligence, 32(1). https://doi.org/10.1609/aaai.v32i1.11448

Issue

Vol. 32 No. 1 (2018): Thirty-Second AAAI Conference on Artificial Intelligence

Section

AAAI Technical Track: Game Theory and Economic Paradigms