Combining Fairness and Optimality when Selecting and Allocating Projects

Khaled Belahcène; Vincent Mousseau; Anaëlle Wilczynski

IJCAI 2021poster12 citations

Combining Fairness and Optimality when Selecting and Allocating Projects

Khaled Belahcène, Vincent Mousseau, Anaëlle Wilczynski

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.

Agent-based and Multi-agent Systems: Computational Social ChoiceAgent-based and Multi-agent Systems: Resource Allocation

BibTeX

@inproceedings{ijcai2021p6,
  title     = {Combining Fairness and Optimality when Selecting and Allocating Projects},
  author    = {Belahcène, Khaled and Mousseau, Vincent and Wilczynski, Anaëlle},
  booktitle = {Proceedings of the Thirtieth International Joint Conference on
               Artificial Intelligence, {IJCAI-21}},
  publisher = {International Joint Conferences on Artificial Intelligence Organization},
  editor    = {Zhi-Hua Zhou},
  pages     = {38--44},
  year      = {2021},
  month     = {8},
  note      = {Main Track},
  doi       = {10.24963/ijcai.2021/6},
  url       = {https://doi.org/10.24963/ijcai.2021/6},
}