Smart Voting
Authors: Rachael Colley, Umberto Grandi, Arianna Novaro
IJCAI 2020 | Conference PDF | Archive PDF | Plain Text | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Theoretical | We propose a generalisation of liquid democracy in which a voter can either vote directly on the issues at stake, delegate her vote to another voter, or express complex delegations to a set of trusted voters. By requiring a ranking of desirable delegations and a backup vote from each voter, we are able to put forward and compare four algorithms to solve delegation cycles and obtain a final collective decision. ... We investigate further algorithmic properties of our setting in Section 3, and we conclude with a study of ranked delegations to single voters and participation axioms (Section 4). |
| Researcher Affiliation | Academia | Rachael Colley , Umberto Grandi and Arianna Novaro IRIT, University of Toulouse {rachael.colley, umberto.grandi, arianna.novaro}@irit.fr |
| Pseudocode | Yes | Algorithm 1 General unravelling procedure UNRAVEL; Algorithm 2 UPDATE(U); Algorithm 3 UPDATE(DU); Algorithm 4 UPDATE(RU); Algorithm 5 UPDATE(DRU) |
| Open Source Code | No | The paper does not provide any explicit statement or link for open-source code for the described methodology. |
| Open Datasets | No | The paper uses an illustrative example (Example 2) with hypothetical data to explain the unravelling procedures but does not use or provide access to any public or real-world dataset for training, testing, or validation. |
| Dataset Splits | No | The paper does not describe specific training, validation, or test splits for any dataset, as it primarily focuses on theoretical and algorithmic analysis. |
| Hardware Specification | No | The paper does not provide any specific hardware specifications (e.g., GPU/CPU models, memory details) used for running its algorithms or any theoretical experiments. The work focuses on algorithmic analysis. |
| Software Dependencies | No | The paper describes algorithms and their theoretical properties. It does not mention any specific software dependencies or version numbers required to implement or replicate the work. |
| Experiment Setup | No | The paper describes algorithms and their theoretical properties. It does not detail an experimental setup with hyperparameters, training configurations, or system-level settings, as it is not an empirical study. |