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..
Towards Understanding Cooperative Multi-Agent Q-Learning with Value Factorization
Authors: Jianhao Wang, Zhizhou Ren, Beining Han, Jianing Ye, Chongjie Zhang
NeurIPS 2021 | Venue PDF | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Experimental | Finally, to support our theoretical implications in practical realization, we conduct an empirical analysis of state-of-the-art deep multi-agent Q-learning algorithms on didactic examples and a broad set of Star Craft II unit micromanagement tasks. |
| Researcher Affiliation | Academia | Jianhao Wang1 , Zhizhou Ren2 , Beining Han1, Jianing Ye1, Chongjie Zhang1 1Institute for Interdisciplinary Information Sciences, Tsinghua University 2Department of Computer Science, University of Illinois at Urbana-Champaign |
| Pseudocode | Yes | Algorithm 1 Factorized Multi-Agent Fitted Q-Iteration (FMA-FQI) |
| Open Source Code | No | No explicit statement or link providing open-source code for the methodology described in this paper was found. |
| Open Datasets | Yes | We utilize Star Craft Multi-Agent Challenge (SMAC) benchmark [20] |
| Dataset Splits | No | The paper describes the collection of an offline dataset but does not explicitly provide training/validation/test dataset splits with specific percentages, counts, or a detailed splitting methodology for the models evaluated. |
| Hardware Specification | No | No specific hardware details (e.g., GPU/CPU models, memory) used for running experiments were mentioned. |
| Software Dependencies | No | No specific ancillary software details, such as library names with version numbers, were provided. |
| Experiment Setup | No | A detailed description of the experiment setting is deferred to Appendix E. |