Computing Pareto Optimal Committees

Abstract

Selecting a set of alternatives based on the preferences of agents is an important problem in committee selection and beyond. Among the various criteria put forth for desirability of a committee, Pareto optimality is a minimal and important requirement. As asking agents to specify their preferences over exponentially many subsets of alternatives is practically infeasible, we assume that each agent specifies a weak order on single alternatives, from which a preference relation over subsets is derived using some preference extension. We consider four prominent extensions (responsive, leximax, best, and worst). For each of them, we consider the corresponding Pareto optimality notion, and we study the complexity of computing and verifying Pareto optimal outcomes. We also consider strategic issues: for three of the set extensions, we present linear-time, Pareto optimal and strategyproof algorithms that work even for weak preferences. PDF

Cite

Text

Aziz et al. "Computing Pareto Optimal Committees." International Joint Conference on Artificial Intelligence, 2016.

Markdown

[Aziz et al. "Computing Pareto Optimal Committees." International Joint Conference on Artificial Intelligence, 2016.](https://mlanthology.org/ijcai/2016/aziz2016ijcai-computing/)

BibTeX

@inproceedings{aziz2016ijcai-computing,
  title     = {{Computing Pareto Optimal Committees}},
  author    = {Aziz, Haris and Lang, Jérôme and Monnot, Jérôme},
  booktitle = {International Joint Conference on Artificial Intelligence},
  year      = {2016},
  pages     = {60-66},
  url       = {https://mlanthology.org/ijcai/2016/aziz2016ijcai-computing/}
}