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- W2076603265 abstract "We consider the optimization problem of a campaign trying to win an election when facing aggregate uncertainty, where agents' voting probabilities are uncertain. Even a small amount of uncertainty will in a large electorate eliminate many of counterintuitive results that arise when voting probabilities are known. In particular, a campaign that can affect the voting probabilities of a fraction of the electorate should maximize the expected difference between its candidate's and the opposing candidate's share of the fraction's potential vote. When a campaign can target only finitely many voters, maximization of the same objective function remains optimal if a convergence condition is satisfied. When voting probabilities are certain, this convergence condition obtains only at knife-edge combinations of parameters, but when voting probabilities are uncertain the condition is necessarily satisfied." @default.
- W2076603265 created "2016-06-24" @default.
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- W2076603265 date "2011-01-01" @default.
- W2076603265 modified "2023-09-25" @default.
- W2076603265 title "How to Win a Large Election" @default.
- W2076603265 doi "https://doi.org/10.2139/ssrn.1417690" @default.
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