On Fair Division under Heterogeneous Matroid Constraints
Authors: Amitay Dror, Michal Feldman, Erel Segal-Halevi5312-5320
AAAI 2021 | Conference PDF | Archive PDF | Plain Text | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Theoretical | In this work, we make progress on this problem by providing positive and negative results for different matroid and valuation types. Among other results, we devise poly-time algorithms for finding EF1 allocations in the following settings: (i) n agents with heterogeneous partition matroids and heterogeneous binary valuations, (ii) 2 agents with heterogeneous partition matroids and heterogeneous valuations, and (iii) at most 3 agents with heterogeneous binary valuations and identical base-orderable matroids. All of our algorithms run in polynomial-time. |
| Researcher Affiliation | Collaboration | 1Tel Aviv University 2Tel Aviv University, Microsoft Research 3Ariel University |
| Pseudocode | No | Algorithm Iterated Priority Matching. (for pseudo code see full version.) |
| Open Source Code | No | The paper mentions a 'full version' (https://arxiv.org/abs/2010.07280) for missing statements and proofs, but does not explicitly state that source code for the described methodology is available for public access. |
| Open Datasets | No | The paper is theoretical and does not involve empirical studies with datasets. |
| Dataset Splits | No | The paper is theoretical and does not involve empirical studies with datasets, therefore no validation splits are provided. |
| Hardware Specification | No | The paper is theoretical and does not report on experiments, thus no hardware specifications are provided. |
| Software Dependencies | No | The paper is theoretical and does not mention specific software dependencies with version numbers. |
| Experiment Setup | No | The paper is theoretical and does not report on experiments, thus no experimental setup details are provided. |