An analytical and experimental comparison of maximal lottery schemes
Bibliographic Data
| ID | 21470331 |
|---|---|
| Authors | Florian Brandl (0000-0002-3931-3931, Princeton University), Felix Brandt (0000-0002-4179-9897, corresponding author), Christian Stricker (0000-0002-6388-5235) |
| Year | 2022 |
| Volume | 58 |
| Issue | 1 |
| Pages | 5-38 |
| Publication date | 2022-01-01 |
| Peer Reviewed | Yes |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | Social Choice and Welfare (JOURNAL) |
| Journal identifiers | ISSN: 0176-1714 • E-ISSN: 1432-217X |
| Publisher | Springer Science and Business Media LLC (PUBLISHER) |
| DOI | 10.1007/s00355-021-01326-x |
| OpenAlex | W3175624739 |
| Language | EN |
| Citations received | 1 |
| References cited | 36 |
Maximal lottery ( $$ ML $$ ML ) schemes constitute an interesting class of randomized voting rules that were proposed by Peter Fishburn in 1984 and have been repeatedly recommended for practical use. However, the subtle differences between different $$ ML $$ ML schemes are often overlooked. Two canonical subsets of $$ ML $$ ML schemes are "Image missing"schemes (which only depend on unweighted majority comparisons) and "Image missing"schemes (which only depend on weighted majority comparisons). We prove that "Image missing"schemes are the only homogeneous $$ ML $$ ML schemes that satisfy $$ SD $$ SD -efficiency and $$ SD $$ SD -participation, but are also among the most manipulable $$ ML $$ ML schemes. While all $$ ML $$ ML schemes are manipulable and even violate monotonicity, they are never manipulable when a Condorcet winner exists and satisfy a relative notion of monotonicity. We also evaluate the frequency of manipulable preference profiles and the degree of randomization of $$ ML $$ ML schemes via extensive computer simulations. In summary, $$ ML $$ ML schemes are rarely manipulable and often do not randomize at all, especially for few alternatives. The average degree of randomization of "Image missing"schemes is consistently lower than that of "Image missing"schemes
Algorithm · Machine learning · Auction Theory and Applications · Computer Science · Game Theory and Voting Systems · Mathematics · Sports Analytics and Performance · Artificial Intelligence
| Unique citing works | 1 |
|---|---|
| Citations per year | 1 |
| Citation span | 2026 - 2026 (1) |
| Citation velocity | current |
| Highly cited | No |
| Citation types | Neutral: 1 |