Project-Fair and Truthful Mechanisms for Budget Aggregation
Authors: Rupert Freeman, Ulrike Schmidt-Kraepelin
AAAI 2024 | Conference PDF | Archive PDF | Plain Text | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Theoretical | We study the budget aggregation problem in which a set of strategic voters must split a finite divisible resource (such as money or time) among a set of competing projects. Our goal is twofold: We seek truthful mechanisms that provide fairness guarantees to the projects. For the first objective, we focus on the class of moving phantom mechanisms, which are to this day essentially the only known truthful mechanisms in this setting. For project fairness, we consider the mean division as a fair baseline, and bound the maximum difference between the funding received by any project and this baseline. We propose a novel and simple moving phantom mechanism that provides optimal project fairness guarantees. As a corollary of our results, we show that our new mechanism minimizes the ℓ1 distance to the mean for three projects and gives the first non-trivial bounds on this quantity for more than three projects. |
| Researcher Affiliation | Academia | Rupert Freeman1, Ulrike Schmidt-Kraepelin2 1University of Virginia, Charlottesville, VA, USA 2TU Eindhoven, The Netherlands freemanr@darden.virginia.edu, u.schmidt.kraepelin@tue.nl |
| Pseudocode | No | The paper does not contain structured pseudocode or algorithm blocks. |
| Open Source Code | No | The paper does not include an unambiguous statement about releasing code for the described methodology or a direct link to a code repository. |
| Open Datasets | No | The paper describes theoretical mechanism design and does not use or refer to publicly available datasets for training experiments. |
| Dataset Splits | No | The paper describes theoretical mechanism design and does not specify training, validation, or test dataset splits. |
| Hardware Specification | No | The paper describes theoretical work and does not mention specific hardware used for experiments. |
| Software Dependencies | No | The paper describes theoretical work and does not list specific software dependencies with version numbers. |
| Experiment Setup | No | The paper focuses on theoretical analysis and does not describe an experimental setup with hyperparameters or system-level training settings. |