Fair Rent Division on a Budget
Authors: Ariel Procaccia, Rodrigo Velez, Dingli Yu
AAAI 2018 | Conference PDF | Archive PDF | Plain Text | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Theoretical | By contrast, we design a polynomial-time algorithm that takes budget constraints as part of its input; it determines whether there exist envy-free allocations that satisfy the budget constraints, and, if so, computes one that optimizes an additional criterion of justice.In Section 3, we construct a polynomial-time (LP-based) algorithm that computes an optimal allocation with respect to a given (linear) criterion of justice, subject to the envy-freeness constraints and the given budget constraints, when a feasible allocation exists. |
| Researcher Affiliation | Academia | Ariel D. Procaccia Computer Science Department Carnegie Mellon University Rodrigo A. Velez Department of Economics Texas A&M University Dingli Yu Institute for Interdisciplinary Information Sciences Tsinghua University |
| Pseudocode | Yes | Algorithm 1: Maximum-rent envy-free allocation in a fully connected economy.Algorithm 2: Optimal envy-free allocation subject to budget constraints. |
| Open Source Code | No | The paper does not provide a link to the source code for the methodology described in this paper. It mentions Spliddit.org as an application but not its own code. |
| Open Datasets | No | This paper is theoretical and does not use datasets for training or evaluation. |
| Dataset Splits | No | This paper is theoretical and does not involve dataset splits for validation. |
| Hardware Specification | No | This paper is theoretical and does not describe experiments, therefore no hardware specifications are mentioned. |
| Software Dependencies | No | This paper is theoretical and does not specify software dependencies with version numbers. |
| Experiment Setup | No | This paper is theoretical and does not describe an experimental setup with hyperparameters or training configurations. |