Independence of Irrelevant Alternatives under the Lens of Pairwise Distortion
Authors: Théo Delemazure, Jérôme Lang, Grzegorz Pierczyński
AAAI 2024 | Conference PDF | Archive PDF | Plain Text | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Experimental | Our contribution is threefold: (1) we provide a new tool to measure the impact of IIA on social welfare (pairwise distortion), based on the well-established notion of voting distortion, (2) we study the average impact of IIA in both general and metric settings, with experiments on synthetic data, and its impact with real datasets; and (3) we study the worst-case impact of IIA in the 1D-Euclidean metric space. |
| Researcher Affiliation | Academia | Th eo Delemazure1, J erˆome Lang1, Grzegorz Pierczy nski2 1 CNRS, Paris Dauphine University, PSL 2 University of Warsaw |
| Pseudocode | No | The paper does not contain structured pseudocode or algorithm blocks (clearly labeled algorithm sections or code-like formatted procedures). |
| Open Source Code | No | The paper does not provide concrete access to source code (specific repository link, explicit code release statement, or code in supplementary materials) for the methodology described in this paper. |
| Open Datasets | Yes | Bars In the unconstrained setting, we investigate the empirical distortion of the Bars dataset (Lesser et al. 2017) from the Preflib database (Mattei and Walsh 2013). |
| Dataset Splits | No | The paper mentions sampling profiles and using datasets but does not provide specific details on train/validation/test splits, percentages, or cross-validation methodology needed for reproduction. |
| Hardware Specification | No | The paper does not provide specific hardware details (exact GPU/CPU models, processor types with speeds, memory amounts, or detailed computer specifications) used for running its experiments. |
| Software Dependencies | No | The paper does not provide specific ancillary software details (e.g., library or solver names with version numbers like Python 3.8, CPLEX 12.4) needed to replicate the experiment. |
| Experiment Setup | No | The paper mentions using profiles of '30 voters and up to 15 alternatives' and varying 'n' and 'm' for experiments, but it does not provide concrete hyperparameter values, optimizer settings, or detailed system-level training configurations. |