An Experimental Comparison of Multiwinner Voting Rules on Approval Elections
Authors: Piotr Faliszewski, Martin Lackner, Krzysztof Sornat, Stanisław Szufa
IJCAI 2023 | Conference PDF | Archive PDF | Plain Text | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Experimental | In this paper, we experimentally compare major approval-based multiwinner voting rules. |
| Researcher Affiliation | Academia | 1AGH University, Poland 2TU Wien, Austria 3IDSIA, USI-SUPSI, Switzerland |
| Pseudocode | No | The paper describes algorithms conceptually but does not include structured pseudocode or algorithm blocks. |
| Open Source Code | Yes | The code for the experiments is available at https://github.com/ Project-PRAGMA/Map-of-Rules-IJCAI-2023. |
| Open Datasets | Yes | We also use real-life participatory budgeting (PB) data from Pabulib [Stolicki et al., 2020] |
| Dataset Splits | No | The paper describes generating instances from statistical cultures and selecting a subset from a real-life dataset, but does not specify explicit training/validation/test splits of these instances. |
| Hardware Specification | No | No specific hardware details (such as GPU/CPU models, processor types, or memory amounts) used for running experiments are mentioned in the paper. |
| Software Dependencies | Yes | in our experiments we use the implementations of the rules provided in the abcvoting library [Lackner et al., 2023]. The reference indicates 'Journal of Open Source Software, 8(81):4880, 2023'. |
| Experiment Setup | Yes | We generated 6000 instances with 100 candidates and 100 voters from the six following statistical cultures (1000 elections per culture): 1D-Euclidean with r = 0.05, 2DEuclidean with r = 0.2, resampling with p = 0.1 and ϕ {0, 1 999, 2 999, . . . , 998 999, 1}, disjoint with p = 0.1, ϕ {0, 1 999, 2 999, . . . , 998 999, 1}, and g = 10, party-list with g = 10, and the Pabulib model. For all instances, we use a committee size of k = 10. |