Preference Restrictions in Computational Social Choice: Recent Progress
Authors: Edith Elkind, Martin Lackner, Dominik Peters
IJCAI 2016 | Conference PDF | Archive PDF | Plain Text | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Theoretical | The goal of this short paper is to provide an overview of recent progress in understanding and exploiting useful properties of restricted preference domains, such as, e.g., the domains of singlepeaked, single-crossing and 1-Euclidean preferences. The goal of this paper is to discuss both of these strands of algorithmic results, as well as to provide pointers to the literature; a longer literature survey that covers this area in further detail is in preparation. |
| Researcher Affiliation | Academia | Edith Elkind University of Oxford United Kingdom elkind@cs.ox.ac.uk Martin Lackner University of Oxford United Kingdom martin.lackner@cs.ox.ac.uk Dominik Peters University of Oxford United Kingdom dominik.peters@cs.ox.ac.uk |
| Pseudocode | No | The paper describes algorithms conceptually but does not include any pseudocode or clearly labeled algorithm blocks. |
| Open Source Code | No | The paper is a survey and does not present new methods requiring source code release. It does not provide any links to open-source code for the work described. |
| Open Datasets | No | The paper is a theoretical survey and does not use or reference any publicly available datasets for training or experimentation. |
| Dataset Splits | No | The paper is a theoretical survey and does not describe training/validation/test dataset splits as it does not conduct experiments. |
| Hardware Specification | No | The paper is a theoretical survey and does not conduct experiments, therefore, no hardware specifications are provided. |
| Software Dependencies | No | The paper is a theoretical survey and does not conduct experiments, therefore, no software dependencies with version numbers are listed. |
| Experiment Setup | No | The paper is a theoretical survey and does not conduct experiments, therefore, no experimental setup details such as hyperparameters are provided. |