Participatory Budgeting with Donations and Diversity Constraints
Authors: Jiehua Chen, Martin Lackner, Jan Maly9323-9330
AAAI 2022 | Conference PDF | Archive PDF | Plain Text | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Theoretical | To sum up, our work provides a first axiomatic and computational analysis of PB with donations and diversity constraints, in the form of both upper and lower bounds. We discuss features and pitfalls of this idea, propose methods to handle donations, and analyze their computational demands. |
| Researcher Affiliation | Academia | TU Wien, Vienna, Austria |
| Pseudocode | Yes | Algorithm 1: Sequential-R(I) |
| Open Source Code | No | The paper states, "Due to space limits, most proofs are deferred to (Chen, Lackner, and Maly 2021)," referencing a technical report on arXiv. This is not an explicit statement of releasing source code for the methodology or a direct link to a code repository. |
| Open Datasets | No | The paper is theoretical and does not involve experiments with datasets, thus no dataset is mentioned as publicly available or open for training. |
| Dataset Splits | No | The paper is theoretical and does not involve experiments or data splits for training, validation, or testing. |
| Hardware Specification | No | The paper is theoretical and does not describe any experiments that would require hardware specifications. |
| Software Dependencies | No | The paper is theoretical and does not describe any experiments that would require software dependencies with specific version numbers. |
| Experiment Setup | No | The paper is theoretical and does not describe any empirical experiments or their setup, therefore, no hyperparameters or system-level training settings are provided. |