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How Hard Is Bribery in Elections

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TLDR
The complexity of influencing elections through bribery was studied in this paper, where the complexity of determining whether by a certain amount of bribing voters a specified candidate can be made the election's winner was studied.
Abstract
We study the complexity of influencing elections through bribery: How computationally complex is it for an external actor to determine whether by a certain amount of bribing voters a specified candidate can be made the election's winner? We study this problem for election systems as varied as scoring protocols and Dodgson voting, and in a variety of settings regarding homogeneous-vs.-nonhomogeneous electorate bribability, bounded-size-vs.-arbitrary-sized candidate sets, weighted-vs.-unweighted voters, and succinct-vs.-nonsuccinct input specification. We obtain both polynomial-time bribery algorithms and proofs of the intractability of bribery, and indeed our results show that the complexity of bribery is extremely sensitive to the setting. For example, we find settings in which bribery is NP-complete but manipulation (by voters) is in P, and we find settings in which bribing weighted voters is NP-complete but bribing voters with individual bribe thresholds is in P. For the broad class of elections (including plurality, Borda, k-approval, and veto) known as scoring protocols, we prove a dichotomy result for bribery of weighted voters: We find a simple-to-evaluate condition that classifies every case as either NP-complete or in P.

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BookDOI

Handbook of Computational Social Choice

TL;DR: This handbook, written by thirty-six prominent members of the computational social choice community, covers the field comprehensively and offers detailed introductions to each of the field's major themes.
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Llull and Copeland voting computationally resist bribery and constructive control

TL;DR: Among systems with a polynomial-time winner problem, Copeland voting is the first natural election system proven to have full resistance to constructive control and vulnerability results for microbribery are proven via a novel technique involving min-cost network flow.
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AI’s War on Manipulation: Are We Winning?

TL;DR: An overview of more than two decades of work that studies computational complexity as a barrier against manipulation in elections is provided.
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Using complexity to protect elections

TL;DR: Computational complexity may truly be the shield against election manipulation.

Computational Social Choice

Felix Brandt, +1 more
TL;DR: The Gibbard-Satterthwaite Impossibility and Computational Hardness of Manipulation as mentioned in this paper are two of the main obstacles in voting rule-based election process, and they have been studied extensively in the literature.
References
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