Approximating weighted and priced bribery in scoring rules

Orgad Keller, Avinatan Hassidim, Noam Hazon

Research output: Contribution to journalArticlepeer-review

3 Scopus citations

Abstract

The classic Bribery problem is to find a minimal subset of voters who need to change their vote to make some preferred candidate win. Its important generalizations consider voters who are weighted and also have different prices. We provide an approximate solution for these problems for a broad family of scoring rules (which includes Borda, t-approval, and Dowdall), in the following sense: For constant weights and prices, if there exists a strategy which costs Ψ, we efficiently fid a strategy which costs at most Ψ+ eO (√Ψ). An extension for non-constant weights and prices is also given. Our algorithm is based on a randomized reduction from these Bribery generalizations to weighted coalitional manipulation (WCM). To solve this WCM instance, we apply the Birkhoff-von Neumann (BvN) decomposition to a fractional manipulation matrix. This allows us to limit the size of the possible ballot search space reducing it from exponential to polynomial, while still obtaining good approximation guarantees. Finding a solution in the truncated search space yields a new algorithm for WCM, which is of independent interest.

Original languageEnglish
Pages (from-to)1057-1098
Number of pages42
JournalJournal of Artificial Intelligence Research
Volume66
DOIs
StatePublished - 1 Dec 2019

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© 2019 AI Access Foundation.

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