Abstract
Studying the computational complexity and designing fast algorithms for determining winners under voting rules are classical and fundamental questions in computational social choice. In this paper, we accelerate voting by leveraging quantum computation: we propose a quantum-accelerated voting algorithm that can be applied to any anonymous voting rule. We show that our algorithm can be quadratically faster than any classical algorithm (based on sampling with replacement) under a wide range of common voting rules, including positional scoring rules, Copeland, and single transferable voting (STV). Precisely, our quantum-accelerated voting algorithm outputs the correct winner with high probability in (Equation presented) time, where n is the number of votes and MoV is margin of victory, the smallest number of voters to change the winner. In contrast, any classical voting algorithm based on sampling with replacement requires (Equation presented) time under a large class of voting rules. Our theoretical results are supported by experiments under plurality, Borda, Copeland, and STV.
| Original language | English |
|---|---|
| Pages (from-to) | 1274-1283 |
| Number of pages | 10 |
| Journal | Proceedings of Machine Learning Research |
| Volume | 216 |
| State | Published - 2023 |
| Event | 39th Conference on Uncertainty in Artificial Intelligence, UAI 2023 - Pittsburgh, United States Duration: Jul 31 2023 → Aug 4 2023 |
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