Fair Division with Prioritized Agents
Authors: Xiaolin Bu, Zihao Li, Shengxin Liu, Jiaxin Song, Biaoshuai Tao
AAAI 2023 | Conference PDF | Archive PDF | Plain Text | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Theoretical | We consider the fair division problem of indivisible items. It is well-known that an envy-free allocation may not exist, and a relaxed version of envy-freeness, envy-freeness up to one item (EF1), has been widely considered. ... We propose a new fairness notion named envy-freeness with prioritized agents EFPRIOR, and study the existence and the algorithmic aspects for the problem of computing an EFPRIOR allocation. ... In particular, we present a polynomialtime algorithm that outputs an EFPRIOR allocation with most of the items allocated. When all the items need to be allocated, we also present polynomial-time algorithms for some well-motivated special cases. |
| Researcher Affiliation | Academia | 1 School of Electronic Information and Electrical Engineering, Shanghai Jiao Tong University 2 School of Physical and Mathematical Sciences, Nanyang Technological University 3 School of Computer Science and Technology, Harbin Institute of Technology, Shenzhen |
| Pseudocode | Yes | Algorithm 1: Algorithm for computing EFPRIOR allocation satisfying Theorem 7 Algorithm 2: Computing a partial EFPRIOR allocation Algorithm 3: The Update Rules U0 and U1. Algorithm 4: The Update Rule U2 Algorithm 5: The Update Rule U3. |
| Open Source Code | No | The paper does not provide a statement or link indicating that open-source code for the described methodology is available. |
| Open Datasets | No | The paper is theoretical and focuses on algorithms and proofs for fair division problems. It does not describe any empirical experiments involving training data or datasets. |
| Dataset Splits | No | The paper is theoretical and focuses on algorithms and proofs for fair division problems. It does not describe any empirical experiments involving dataset splits for validation. |
| Hardware Specification | No | The paper is theoretical and focuses on algorithms and proofs. It does not describe any empirical experiments that would require specifying hardware used. |
| Software Dependencies | No | The paper is theoretical and focuses on algorithms and proofs. It does not describe any empirical experiments that would require specifying software dependencies with version numbers. |
| Experiment Setup | No | The paper is theoretical and focuses on algorithms and proofs. It does not describe any empirical experiments, hyperparameters, or training configurations for an experimental setup. |