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Conference Papers Year : 2017

A Game-Theoretic View of Randomized Fair Multi-Agent Optimization

Hugo Gilbert
Olivier Spanjaard

Abstract

We tackle fair multi-agent optimization problems and use a generalized Gini index to determine a fair and efficient solution. We claim that considering mixed solutions (i.e., lotteries over solutions) enables to enhance the fairness of an optimal solution. Interpreting a fair multi-agent optimization problem as a zero-sum two-player game between an optimization player choosing a solution and an adversary which has some control over the payoffs of the game, we propose two methods (a cutting-plane method and a double oracle method) to compute an optimal mixed solution. Numerical tests are provided to compare their efficiency.
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Dates and versions

hal-01560545 , version 1 (11-07-2017)

Identifiers

  • HAL Id : hal-01560545 , version 1

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Hugo Gilbert, Olivier Spanjaard. A Game-Theoretic View of Randomized Fair Multi-Agent Optimization. The 3rd IJCAI Algorithmic Game Theory Workshop, Aug 2017, Melbourne, Australia. ⟨hal-01560545⟩
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