Research map / Learning theory and algorithms / Submodular and game algorithms
Computational Analyses of the Electoral College: Campaigning Is Hard But Approximately Manageable
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Measured effects reported in the paper
| What was changed | Where | Measured | Effect |
|---|---|---|---|
| Use an approximate best-response algorithm and allow a constant-factor increase in troop use | General multifaceted Colonel Blotto games · General multifaceted Colonel Blotto games | maxmin payoff approximation: (O( ln(1/ϵ) ϵ ), ϵ)-maxmin | Helped |
| Exploit homogeneous battlegrounds and allow each troop to be used 1+ϵ times | Symmetric multifaceted Colonel Blotto games · Symmetric multifaceted Colonel Blotto games | maxmin payoff approximation: (1+ϵ, 0)-maxmin | Helped |
| Reduce maxmin computation to approximate best-response computation using the Ellipsoid method | Huge constant-sum games · Multifaceted Colonel Blotto games | maxmin payoff approximation: (α, 2·(1−1/β)) | Helped |
| Use multifaceted, battleground-dependent resource strengths rather than homogeneous troops | Multifaceted Colonel Blotto games · Multifaceted Colonel Blotto games | best-response approximation feasibility | Hurt |
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