Power in Liquid Democracy
Authors: Yuzhe Zhang, Davide Grossi5822-5830
AAAI 2021 | Conference PDF | Archive PDF | Plain Text | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Experimental | Finally, we simulate our game theoretic model and study how two key parameters of the model influence the distribution of power both in equilibrium and after one-shot interaction. |
| Researcher Affiliation | Academia | Yuzhe Zhang1, Davide Grossi1,2 1University of Groningen 2University of Amsterdam |
| Pseudocode | Yes | Further details on the setup of our experiments, including pseudo-code for the algorithms of OSI and IRBD are provided in the appendix. |
| Open Source Code | No | The paper provides a link to an arXiv preprint ("2https://arxiv.org/pdf/2010.07070.pdf") which is a full version of the paper, not a code repository. It does not explicitly state that source code is available or provide a link to it. |
| Open Datasets | No | The paper states, "we use an accuracy vector Q R30, where each element in Q is drawn from a Gaussian distribution N(0.75, 0.125)," indicating synthetically generated data rather than a publicly available dataset with concrete access information. |
| Dataset Splits | No | The paper describes generating synthetic data for its experiments but does not specify training, validation, or test dataset splits. It mentions random sampling of coalitions for DB estimation, which is not a dataset split. |
| Hardware Specification | No | The paper does not provide any specific details about the hardware used for running its experiments, such as CPU or GPU models, or memory specifications. |
| Software Dependencies | No | The paper mentions implementing an "approximation method described by Bachrach et al. (2008)" but does not list any specific software or library dependencies with version numbers. |
| Experiment Setup | Yes | We set |N| = 30, the quota β = 16, and for each parameter setting, we use an accuracy vector Q R30, where each element in Q is drawn from a Gaussian distribution N(0.75, 0.125). All statistics are the mean value over 50 instances for each parameter setting. |