Approximately EFX Allocations for Indivisible Chores
Authors: Shengwei Zhou, Xiaowei Wu
IJCAI 2022 | Conference PDF | Archive PDF | Plain Text | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Theoretical | In this paper, we propose polynomial-time algorithms for the computation of approximately EFX allocations for indivisible chores. For three agents, our algorithm achieves an approximation ratio of 5 while for n 4 agents the approximation ratio is 3n2. Prior to our work, no non-trivial results regarding the approximation of EFX allocation for chores are known, except for some special cases [Li et al., 2022]. |
| Researcher Affiliation | Academia | Shengwei Zhou , Xiaowei Wu IOTSC, University of Macau {yc17423, xiaoweiwu}@um.edu.mo, |
| Pseudocode | Yes | Algorithm 1: Sequential Placement; Algorithm 2: Algorithm for 2 Large Agents; Algorithm 3: Algorithm for 3 Large Agents |
| Open Source Code | No | The paper does not contain any explicit statements or links indicating that source code for the described methodology is publicly available. |
| Open Datasets | No | The paper is theoretical and does not involve empirical experiments with datasets. Therefore, no information about public datasets or their access is provided. |
| Dataset Splits | No | The paper is theoretical and does not involve empirical experiments with data. Thus, there is no discussion of training, validation, or test dataset splits. |
| Hardware Specification | No | The paper is theoretical and does not describe computational experiments. Therefore, no hardware specifications are mentioned. |
| Software Dependencies | No | The paper is theoretical and focuses on algorithm design and proofs; it does not describe empirical experiments that would require specific software dependencies with version numbers. |
| Experiment Setup | No | The paper is theoretical and does not include details on experimental setup, hyperparameter values, or system-level training settings as it does not conduct empirical experiments. |