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Conference papers

Combining Fairness and Optimality when Selecting and Allocating Projects

Abstract : We consider the problem of the conjoint selection and allocation of projects to a population of agents, e.g. students are assigned papers and shall present them to their peers. The selection can be constrained either by quotas over subcategories of projects, or by the preferences of the agents themselves. We explore fairness and optimality issues and refine the analysis of the rank-maximality and popularity optimality concepts. We show that they are compatible with reasonable fairness requirements related to rank-based envy-freeness and can be adapted to select globally good projects according to the preferences of the agents.
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https://hal.archives-ouvertes.fr/hal-03312854
Contributor : Anaëlle Wilczynski Connect in order to contact the contributor
Submitted on : Tuesday, August 3, 2021 - 1:34:05 AM
Last modification on : Monday, December 20, 2021 - 12:06:26 PM

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Khaled Belahcene, Vincent Mousseau, Anaëlle Wilczynski. Combining Fairness and Optimality when Selecting and Allocating Projects. 30th International Joint Conference on Artificial Intelligence (IJCAI-21), Aug 2021, Montreal, Canada. pp.38-44, ⟨10.24963/ijcai.2021/6⟩. ⟨hal-03312854⟩

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