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Lower Bound Issues in Computational Social Choice

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Gives concrete complexity boundaries: lobbying on voter-by-issue matrices is FPT via Lenstra-style ILP when parameterized by the maximum number of ones per column and by the number of allowed row changes, but exhibits intermediate hardness captured by log-SNP for intermediate hardness; shift-bribery with scaled prices admits a polynomial-time/FPT regime for practical pricing models; districting/gerrymandering problems are NP-complete via a reduction from Exact Cover by 3-Set even for tiny fixed district sizes, so many natural variants stay intractable.

AI-written summary · about

  1. 0:00Start
  2. 0:29What is Computational Social Choice?
  3. 1:38Motivation
  4. 3:57Motivating Example: Sequential Voting!
  5. 18:11Lobbying: ILP-Based FPT (Lenstra) IV
  6. 32:31Shift Bribery: FPT Approximation III
  7. 35:14Combinatorial Shift Bribery: Inapproximability
  8. 43:09Network-Based Vertex Dissolution: ParaNP-Hardness IV
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