Computing Pareto Optimal Committees
Proceedings of the Twenty-Fifth International Joint Conference on Artificial Intelligence. Pages 60-65.
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.
@inproceedings{ijcai2016p16,
title = {Computing Pareto Optimal Committees},
author = {Aziz, Haris and Lang, Jérôme and Monnot, Jérôme},
booktitle = {Proceedings of the Twenty-Fifth International Joint Conference on
Artificial Intelligence, {IJCAI-16}},
publisher = {AAAI Press / International Joint Conferences on Artificial Intelligence},
editor = {Subbarao Kambhampati},
pages = {60--65},
year = {2016},
month = {7},
url = {https://ijcai.org/proceedings/2016/16},
}
TY - CPAPER TI - Computing Pareto Optimal Committees AU - Aziz, Haris AU - Lang, Jérôme AU - Monnot, Jérôme T2 - Proceedings of the Twenty-Fifth International Joint Conference on Artificial Intelligence, IJCAI-16 PB - AAAI Press / International Joint Conferences on Artificial Intelligence PY - 2016 SP - 60 EP - 65 UR - https://ijcai.org/proceedings/2016/16 ER -Copied
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