Approximation and hardness of shift-bribery

Piotr Faliszewski; Pasin Manurangsi; Krzysztof Sornat

doi:10.1609/aaai.v33i01.33011901

Approximation and hardness of shift-bribery

Piotr Faliszewski
, Pasin Manurangsi
, Krzysztof Sornat

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

10 Scopus citations

Abstract

In the SHIFT-BRIBERY problem we are given an election, a preferred candidate, and the costs of shifting this preferred candidate up the voters' preference orders. The goal is to find such a set of shifts that ensures that the preferred candidate wins the election. We give the first polynomial-time approximation scheme for the case of positional scoring rules, and for the Copeland rule we show strong inapproximability results.

Original language	English
Title of host publication	33rd AAAI Conference on Artificial Intelligence, AAAI 2019, 31st Innovative Applications of Artificial Intelligence Conference, IAAI 2019 and the 9th AAAI Symposium on Educational Advances in Artificial Intelligence, EAAI 2019
Publisher	AAAI press
Pages	1901-1908
Number of pages	8
ISBN (Electronic)	9781577358091
DOIs	https://doi.org/10.1609/aaai.v33i01.33011901
State	Published - 1 Jan 2019
Externally published	Yes
Event	33rd AAAI Conference on Artificial Intelligence, AAAI 2019, 31st Annual Conference on Innovative Applications of Artificial Intelligence, IAAI 2019 and the 9th AAAI Symposium on Educational Advances in Artificial Intelligence, EAAI 2019 - Honolulu, United States Duration: 27 Jan 2019 → 1 Feb 2019

Publication series

Name	33rd AAAI Conference on Artificial Intelligence, AAAI 2019, 31st Innovative Applications of Artificial Intelligence Conference, IAAI 2019 and the 9th AAAI Symposium on Educational Advances in Artificial Intelligence, EAAI 2019

Conference

Conference	33rd AAAI Conference on Artificial Intelligence, AAAI 2019, 31st Annual Conference on Innovative Applications of Artificial Intelligence, IAAI 2019 and the 9th AAAI Symposium on Educational Advances in Artificial Intelligence, EAAI 2019
Country/Territory	United States
City	Honolulu
Period	27/01/19 → 1/02/19

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 16 Peace, Justice and Strong Institutions

ASJC Scopus subject areas

Artificial Intelligence

Access to Document

10.1609/aaai.v33i01.33011901

Cite this

Faliszewski, P., Manurangsi, P., & Sornat, K. (2019). Approximation and hardness of shift-bribery. In 33rd AAAI Conference on Artificial Intelligence, AAAI 2019, 31st Innovative Applications of Artificial Intelligence Conference, IAAI 2019 and the 9th AAAI Symposium on Educational Advances in Artificial Intelligence, EAAI 2019 (pp. 1901-1908). (33rd AAAI Conference on Artificial Intelligence, AAAI 2019, 31st Innovative Applications of Artificial Intelligence Conference, IAAI 2019 and the 9th AAAI Symposium on Educational Advances in Artificial Intelligence, EAAI 2019). AAAI press. https://doi.org/10.1609/aaai.v33i01.33011901

Faliszewski, Piotr ; Manurangsi, Pasin ; Sornat, Krzysztof. / Approximation and hardness of shift-bribery. 33rd AAAI Conference on Artificial Intelligence, AAAI 2019, 31st Innovative Applications of Artificial Intelligence Conference, IAAI 2019 and the 9th AAAI Symposium on Educational Advances in Artificial Intelligence, EAAI 2019. AAAI press, 2019. pp. 1901-1908 (33rd AAAI Conference on Artificial Intelligence, AAAI 2019, 31st Innovative Applications of Artificial Intelligence Conference, IAAI 2019 and the 9th AAAI Symposium on Educational Advances in Artificial Intelligence, EAAI 2019).

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title = "Approximation and hardness of shift-bribery",

abstract = "In the SHIFT-BRIBERY problem we are given an election, a preferred candidate, and the costs of shifting this preferred candidate up the voters' preference orders. The goal is to find such a set of shifts that ensures that the preferred candidate wins the election. We give the first polynomial-time approximation scheme for the case of positional scoring rules, and for the Copeland rule we show strong inapproximability results.",

author = "Piotr Faliszewski and Pasin Manurangsi and Krzysztof Sornat",

note = "Publisher Copyright: {\textcopyright} 2019, Association for the Advancement of Artificial Intelligence (www.aaai.org). All rights reserved.; 33rd AAAI Conference on Artificial Intelligence, AAAI 2019, 31st Annual Conference on Innovative Applications of Artificial Intelligence, IAAI 2019 and the 9th AAAI Symposium on Educational Advances in Artificial Intelligence, EAAI 2019 ; Conference date: 27-01-2019 Through 01-02-2019",

year = "2019",

month = jan,

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doi = "10.1609/aaai.v33i01.33011901",

language = "English",

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pages = "1901--1908",

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Faliszewski, P, Manurangsi, P & Sornat, K 2019, Approximation and hardness of shift-bribery. in 33rd AAAI Conference on Artificial Intelligence, AAAI 2019, 31st Innovative Applications of Artificial Intelligence Conference, IAAI 2019 and the 9th AAAI Symposium on Educational Advances in Artificial Intelligence, EAAI 2019. 33rd AAAI Conference on Artificial Intelligence, AAAI 2019, 31st Innovative Applications of Artificial Intelligence Conference, IAAI 2019 and the 9th AAAI Symposium on Educational Advances in Artificial Intelligence, EAAI 2019, AAAI press, pp. 1901-1908, 33rd AAAI Conference on Artificial Intelligence, AAAI 2019, 31st Annual Conference on Innovative Applications of Artificial Intelligence, IAAI 2019 and the 9th AAAI Symposium on Educational Advances in Artificial Intelligence, EAAI 2019, Honolulu, United States, 27/01/19. https://doi.org/10.1609/aaai.v33i01.33011901

Approximation and hardness of shift-bribery. / Faliszewski, Piotr; Manurangsi, Pasin; Sornat, Krzysztof.
33rd AAAI Conference on Artificial Intelligence, AAAI 2019, 31st Innovative Applications of Artificial Intelligence Conference, IAAI 2019 and the 9th AAAI Symposium on Educational Advances in Artificial Intelligence, EAAI 2019. AAAI press, 2019. p. 1901-1908 (33rd AAAI Conference on Artificial Intelligence, AAAI 2019, 31st Innovative Applications of Artificial Intelligence Conference, IAAI 2019 and the 9th AAAI Symposium on Educational Advances in Artificial Intelligence, EAAI 2019).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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Faliszewski P, Manurangsi P, Sornat K. Approximation and hardness of shift-bribery. In 33rd AAAI Conference on Artificial Intelligence, AAAI 2019, 31st Innovative Applications of Artificial Intelligence Conference, IAAI 2019 and the 9th AAAI Symposium on Educational Advances in Artificial Intelligence, EAAI 2019. AAAI press. 2019. p. 1901-1908. (33rd AAAI Conference on Artificial Intelligence, AAAI 2019, 31st Innovative Applications of Artificial Intelligence Conference, IAAI 2019 and the 9th AAAI Symposium on Educational Advances in Artificial Intelligence, EAAI 2019). doi: 10.1609/aaai.v33i01.33011901

Approximation and hardness of shift-bribery

Abstract

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ASJC Scopus subject areas

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