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Price of Pareto optimality in hedonic games

Abstract:
The Price of Anarchy measures the welfare loss caused by selfish behavior: it is defined as the ratio of the social welfare in a socially optimal outcome and in a worst Nash equilibrium. Similar measures can be derived for other classes of stable outcomes. We observe that Pareto optimality can be seen as a notion of stability: an outcome is Pareto optimal if and only if it does not admit a deviation by the grand coalition that makes all players weakly better off and some players strictly better off. Motivated by this observation, we introduce the concept of Price of Pareto Optimality: this is an analogue of the Price of Anarchy, with the worst Nash equilibrium replaced with the worst Pareto optimal outcome. We then study this concept in the context of hedonic games, and provide lower and upper bounds on the Price of Pareto Optimality in three classes of hedonic games: additively separable hedonic games, fractional hedonic games, and modified fractional hedonic games.
Publication status:
Published
Peer review status:
Peer reviewed

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Publisher copy:
10.1016/j.artint.2020.103357

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Institution:
University of Oxford
Division:
MPLS
Department:
Computer Science
Role:
Author


Publisher:
Elsevier
Journal:
Artificial Intelligence More from this journal
Volume:
288
Article number:
103357
Publication date:
2020-07-27
Acceptance date:
2020-07-16
DOI:
ISSN:
0004-3702


Language:
English
Keywords:
Pubs id:
1123012
Local pid:
pubs:1123012
Deposit date:
2020-07-31
ARK identifier:

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