On Coalitional Manipulation for Multiwinner Elections: Shortlisting
Authors: Robert Bredereck, Andrzej Kaczmarczyk, Rolf Niedermeier
IJCAI 2017 | Conference PDF | Archive PDF | Plain Text | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Theoretical | We provide the first in-depth study of the computational complexity of strategic voting for shortlisting based on the most natural and simple voting rule in this scenario, â„“-Bloc (every voter approves â„“candidates). ... We provide a fairly comprehensive picture of the computational complexity landscape of this neglected scenario. |
| Researcher Affiliation | Academia | Robert Bredereck University of Oxford, United Kingdom; TU Berlin, Germany robert.bredereck@tu-berlin.de Andrzej Kaczmarczyk and Rolf Niedermeier TU Berlin, Germany {a.kaczmarczyk, rolf.niedermeier}@tu-berlin.de |
| Pseudocode | No | The paper describes algorithmic ideas and complexity results in prose, but does not include structured pseudocode or clearly labeled algorithm blocks. |
| Open Source Code | No | The paper does not provide any statement or link indicating the release of source code for the described methodology. |
| Open Datasets | No | The paper is theoretical and does not describe experiments involving datasets for training, validation, or testing. |
| Dataset Splits | No | The paper is theoretical and does not describe experiments involving datasets for training, validation, or testing, thus no dataset split information is provided. |
| Hardware Specification | No | The paper is theoretical and does not describe any computational experiments that would require specific hardware, thus no hardware specifications are provided. |
| Software Dependencies | No | The paper is theoretical and does not describe any computational experiments that would require specific software dependencies with version numbers. |
| Experiment Setup | No | The paper is theoretical and does not describe any experimental setup details such as hyperparameters or system-level training settings. |