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Communication, Distortion, and Randomness in Metric Voting

AAAI 2020 · Learning theory and algorithms › Submodular and game algorithms · approach: Committee voting rules · 30 citations (OpenAlex)

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Measured effects reported in the paper

What was changedWhereMeasuredEffect
Restrict deterministic reports to candidates at k ranking positionsDeterministic k-entry voting rules · Metric voting (n candidates)worst-case distortion: distortion at least \frac{2n-k}{k}Hurt
Restrict each voter's report to b bitsDeterministic communication-bounded voting rules · Metric voting (n candidates)worst-case distortion: distortion at least \frac{2n-4}{b} - 1Hurt
Use the proposed top-k Copeland-style comparison-graph ruleDeterministic top-k voting · Metric voting (n candidates)worst-case distortion: distortion at most \frac{79n}{k}Helped
Mix Proportional to Squares with Random Dictatorship at the stated probabilitiesRandomized first-choice voting · Metric voting (n candidates)expected distortion: 3-\frac{2}{n}Helped

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