Proportionality Guarantees in Elections with Interdependent Issues

Authors: Markus Brill, Evangelos Markakis, Georgios Papasotiropoulos, Jannik Peters

IJCAI 2023 | Conference PDF | Archive PDF | Plain Text | LLM Run Details

Reproducibility Variable Result LLM Response
Research Type Theoretical Our findings indicate that the conditional case poses additional challenges and differs significantly from the unconditional one, both in terms of proportionality guarantees and computational complexity.
Researcher Affiliation Collaboration 1University of Warwick, Coventry, UK 2Athens University of Economics and Business, Athens, Greece 3Input Output Global (IOG) 4TU Berlin, Berlin, Germany
Pseudocode No The paper describes algorithms (Conditional Proportional Approval Voting and Conditional Method of Equal Shares) but does not include structured pseudocode or algorithm blocks.
Open Source Code No The paper does not include an explicit statement about releasing source code for the methodology or a link to a code repository.
Open Datasets No The paper is theoretical and focuses on mathematical proofs and analysis of voting rules; it does not use or reference any datasets for training or evaluation.
Dataset Splits No The paper is theoretical and does not involve empirical experiments with dataset splits (training, validation, test).
Hardware Specification No The paper is theoretical and does not describe any specific hardware used for experiments.
Software Dependencies No The paper is theoretical and does not specify any ancillary software or library versions used for implementation or experiments.
Experiment Setup No The paper is theoretical and does not describe an experimental setup with specific hyperparameters or system-level training settings.