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

Hugo Gilbert 1 Olivier Spanjaard 1 
LIP6 - Laboratoire d'Informatique de Paris 6
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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Submitted on : Tuesday, July 11, 2017 - 4:21:19 PM
Last modification on : Sunday, June 26, 2022 - 9:43:15 AM
Long-term archiving on: : Wednesday, January 24, 2018 - 8:42:28 PM


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  • HAL Id : hal-01560545, version 1


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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