Price of Fairness in Budget Division and Probabilistic Social Choice
Authors: Marcin Michorzewski, Dominik Peters, Piotr Skowron2184-2191
AAAI 2020 | Conference PDF | Archive PDF | Plain Text | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Experimental | In this section we extend our approach beyond the worst-case analysis. In a series of computer simulations we assess the average efficiency and egalitarian fairness of randomized rules assuming that voters preferences come from certain distributions. |
| Researcher Affiliation | Academia | 1University of Warsaw, 2Carnegie Mellon University |
| Pseudocode | No | The paper does not contain any pseudocode or clearly labeled algorithm blocks. |
| Open Source Code | No | The paper does not provide any concrete access to open-source code for the methodology described. |
| Open Datasets | No | The paper describes data generation models (Euclidean Model, Impartial Culture, Mallow’s Model) but does not provide access to a specific publicly available or open dataset. |
| Dataset Splits | No | The paper describes drawing instances for simulations but does not specify training, validation, or test dataset splits. |
| Hardware Specification | No | The paper does not provide any specific hardware details used for running its experiments. |
| Software Dependencies | No | The paper does not provide specific ancillary software details with version numbers. |
| Experiment Setup | Yes | For each configuration we draw 500 instances, and for each instance I and each rule f we calculate the normalized welfare sw(I, f(I)). |