Notice: The reproducibility variables underlying each score are classified using an automated LLM-based pipeline, validated against a manually labeled dataset. LLM-based classification introduces uncertainty and potential bias; scores should be interpreted as estimates. Full accuracy metrics and methodology are described in Coakley et alK. L. Coakley, T. Snelleman, H. Hoos, and O. E. Gundersen, "The embrace of open science: An analysis of a decade of AI research and 56 800 conference papers," Under Review, 2026..
Multi-agent Online Scheduling: MMS Allocations for Indivisible Items
Authors: Shengwei Zhou, Rufan Bai, Xiaowei Wu
ICML 2023 | Venue PDF | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Theoretical | For the allocation of goods, we show that no competitive algorithm exists even when there are only three agents and propose an optimal 0.5-competitive algorithm for the case of two agents. For the allocation of chores, we propose a (2 1/n)-competitive algorithm for n 3 agents and a 2 1.414-competitive algorithm for two agents. Besides, we show that no algorithm can do better than 15/11 1.364competitive for two agents. |
| Researcher Affiliation | Academia | 1IOTSC, University of Macau, Macao SAR, China. |
| Pseudocode | Yes | Algorithm 1 Algorithm-for-2-Agents-for-Goods |
| Open Source Code | No | The paper does not mention providing open-source code for the described methodology. |
| Open Datasets | No | The paper focuses on theoretical analysis and does not use or refer to any datasets for training or evaluation. |
| Dataset Splits | No | The paper is theoretical and does not involve data splits for training, validation, or testing. |
| Hardware Specification | No | The paper is theoretical and does not describe any specific hardware used for experiments. |
| Software Dependencies | No | The paper is theoretical and does not specify any software dependencies with version numbers. |
| Experiment Setup | No | The paper focuses on theoretical analysis and algorithm design, therefore it does not include details about experimental setup or hyperparameters. |