Strategyproof Randomized Social Choice for Restricted Sets of Utility Functions
Authors: Patrick Lederer
IJCAI 2021 | Conference PDF | Archive PDF | Plain Text | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Theoretical | The paper focuses on theoretical analysis, definitions, and proving theorems and propositions related to social choice theory and strategyproofness. It does not conduct empirical studies, analyze data, or report metrics from experiments. |
| Researcher Affiliation | Academia | Patrick Lederer Technische Universti at M unchen ledererp@in.tum.de |
| Pseudocode | No | The paper contains formal definitions and theorems but no pseudocode or algorithm blocks. |
| Open Source Code | No | The paper does not mention providing open-source code for the described methodology. |
| Open Datasets | No | This is a theoretical paper and does not involve training models on datasets. |
| Dataset Splits | No | This is a theoretical paper and does not involve dataset splits for validation. |
| Hardware Specification | No | This is a theoretical paper and does not describe any experimental setup or hardware specifications. |
| Software Dependencies | No | This is a theoretical paper and does not mention any software dependencies with specific version numbers. |
| Experiment Setup | No | This is a theoretical paper and does not include details about an experimental setup, hyperparameters, or training configurations. |