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Restricted Preference Domains in Social Choice: Two Perspectives

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Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 11059))

Abstract

Preference aggregation is a challenging task: Arrow’s famous impossibility theorem [1] tells us that there is no perfect voting rule. One of the best-known ways to circumvent this difficulty is to assume that voters’ preferences satisfy a structural constraint, such as, e.g., being single-peaked. Indeed, under this assumption many impossibility results in social choice disappear. Restricted preference domains also play an important role in computational social choice: for instance, there are voting rules that are NP-hard to compute in general, but admit efficient winner determination algorithms when voters’ preferences belong to a restricted domain. However, restricted domains that have nice social choice-theoretic properties are not necessarily attractive from an algorithmic perspective, and vice versa. In this note, we will discuss some domain restrictions that have proved to be useful from a computational perspective, and compare the use of restricted domains in computational and classic social choice theory.

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Acknowledgments

This work was supported by the European Research Council (ERC) under grant number 639945 (ACCORD).

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Correspondence to Edith Elkind .

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Elkind, E. (2018). Restricted Preference Domains in Social Choice: Two Perspectives. In: Deng, X. (eds) Algorithmic Game Theory. SAGT 2018. Lecture Notes in Computer Science(), vol 11059. Springer, Cham. https://doi.org/10.1007/978-3-319-99660-8_2

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  • DOI: https://doi.org/10.1007/978-3-319-99660-8_2

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