Participation Incentives in Approval-Based Committee Elections

Authors: Martin Bullinger, Chris Dong, Patrick Lederer, Clara Mehler

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Reproducibility Variable Result LLM Response
Research Type Theoretical In this paper, we study the participation incentives of ABC voting rules. In more detail, we first investigate which ABC voting rules satisfy participation and prove that all ABC scoring rules (including all Thiele rules) even satisfy group participation. This generalizes the observation that scoring rules satisfy participation for single-winner elections and gives a strong argument in favor of Thiele rules. By contrast, we prove a general impossibility theorem, which shows that most ABC voting rules that sequentially compute the winning committees fail participation.
Researcher Affiliation Academia Martin Bullinger1*, Chris Dong2, Patrick Lederer2, Clara Mehler2 1Department of Computer Science, University of Oxford 2School of Computation, Information and Technology, Technical University of Munich martin.bullinger@cs.ox.ac.uk, chris.dong@tum.de, ledererp@in.tum.de, mehler@in.tum.de
Pseudocode No The paper describes algorithms (e.g., sequential Thiele rules, seq Phragmén, MES) conceptually and with mathematical notation, but it does not present any pseudocode or clearly labeled algorithm blocks.
Open Source Code No The paper does not contain any statements about releasing code for the described methodology, nor does it provide a link to a code repository.
Open Datasets No The paper is theoretical and does not involve empirical experiments using datasets for training. It discusses abstract profiles and voting rules.
Dataset Splits No The paper is theoretical and does not involve empirical experiments with dataset splits for validation or testing.
Hardware Specification No The paper is theoretical and does not describe any computational experiments that would require specific hardware. Therefore, no hardware specifications are mentioned.
Software Dependencies No The paper is theoretical and does not describe any computational experiments that would require specific software with version numbers. Therefore, no software dependencies are mentioned.
Experiment Setup No The paper is theoretical and focuses on mathematical proofs and algorithmic properties of voting rules. It does not include an experimental setup with hyperparameters or system-level training settings.