MILP the Gap: An Automated Reasoning Approach to Condorcet's Paradox
Computational social choice studies how conflicting individual preferences are aggregated into a collective decision, with applications to elections, AI evaluation/alignment, and recommendation systems. We focus on settings where $n$ voters (e.g., human evaluators or algorithmic benchmarks) each rank $m$ alternatives (e.g., human candidates or AI models/outputs), and the goal is to select a committee of $k$ alternatives. One measure of the (in)stability of the outcome is the number of voters who prefer an unchosen alternative to all alternatives in the committee. If this number is less than half the electorate, the committee is a Condorcet winning set, which may not exist if $k \leq 2$. M...
| Authors | Itai Zilberstein, Ruben Martins, Ratip Emin Berker |
|---|---|
| Primary category | cs.GT |
| Published | 21 April 2026 |
| Last updated at source | 10 October 2026 |
Silytics shows public metadata from arXiv and links to the original. Information may be incomplete or out of date. Last refreshed 17 October 2026. Licenses and terms of the original apply to the work itself. Not financial, legal or professional advice.