Plurality Voting Under Uncertainty
Authors: Reshef Meir
AAAI 2015 | Conference PDF | Archive PDF | Plain Text | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Theoretical | The main purpose of this work is to close this gap, and to prove equilibrium existence and convergence under conditions that are as broad as possible.Our main result is proving that voters with local dominance behavior always converge to an equilibrium. This holds for any population of voters with different preferences and uncertainty levels, for any initial voting profile, and for any order of moves (including moves of arbitrary subsets of voters, and suboptimal moves).We showed that in the Plurality voting system, voters who avoid locally-dominated candidates will always converge to an equilibrium, and that this result is robust to the uncertainty levels in the populations, the initial state, and the order in which voters or groups of voters play.We intend to check whether empirical and experimental evidence (e.g. from (Van der Straeten et al. 2010)) support the theory, and if so, what can we say about actual uncertainty levels in real populations. |
| Researcher Affiliation | Academia | Reshef Meir Harvard University |
| Pseudocode | No | No pseudocode or algorithm blocks are provided in the paper. The paper focuses on theoretical proofs and model definitions. |
| Open Source Code | No | Due to space constraints, some of the proofs were omitted, and are available in the full version of this paper.1 In the full version we also show that all of our results hold in the finite case, for voters that move one-at-a-time.1http://arxiv.org/abs/1411.4949 |
| Open Datasets | No | The paper is theoretical and does not involve empirical evaluation or the use of datasets. |
| Dataset Splits | No | The paper is theoretical and does not involve empirical evaluation or the use of datasets, thus no dataset split information is provided. |
| Hardware Specification | No | The paper is theoretical and does not describe any computational experiments conducted by the authors, thus no hardware specifications are provided. |
| Software Dependencies | No | The paper is theoretical and does not describe any software implementation or dependencies with version numbers. |
| Experiment Setup | No | The paper is theoretical and does not describe any experimental setup, hyperparameters, or training settings. |