Research map / Learning theory and algorithms / Submodular and game algorithms
Manipulative Elicitation — A New Attack on Elections with Incomplete Preferences
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Measured effects reported in the paper
| What was changed | Where | Measured | Effect |
|---|---|---|---|
| Permit partial elicitation without candidate-pair minimums | Minimax-regret score-based voting · Manipulative elicitation | computational complexity: polynomial time solvable | Helped |
| Add a minimum-comparability constraint for each candidate pair | Minimax-regret score-based voting · Manipulative elicitation with candidate pair limit | computational complexity: NPC | Hurt |
| Apply candidate-pair limits | Borda · Manipulative elicitation with candidate pair limit | computational complexity: NPC | Hurt |
| Apply candidate-pair limits | Plurality · Manipulative elicitation with candidate pair limit | computational complexity: NPC | Hurt |
| Apply candidate-pair limits | Maximin, Copelandα, and simplified Bucklin · Manipulative elicitation with candidate pair limit | computational complexity: NPC | Hurt |
| Partially elicit preferences to retain target-w comparisons against lower-ranked alternatives | Plurality minimax regret · Plurality election with incomplete preferences | minimax-regret plurality score: n -> (n-1) | Helped |
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