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..
Roles and Teams Hedonic Games
Authors: Matthew Spradling
AAAI 2014 | Venue PDF | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Experimental | We validated the heuristic against brute force optimization with 240 randomly generated RTHG instances, with |P| from 6 to 15, |R| from 3 to 6, and m from 3 to 5. We ran the greedy heuristic on each instance 500 times. We implemented a local search algorithm to construct individually stable solutions for those instances. |
| Researcher Affiliation | Academia | Matthew Spradling University of Kentucky EMAIL |
| Pseudocode | No | The paper describes algorithms verbally but does not include any structured pseudocode or algorithm blocks. |
| Open Source Code | No | The paper does not provide any statement or link indicating the availability of its source code. |
| Open Datasets | No | The paper states it used '240 randomly generated RTHG instances' but does not provide access information (link, DOI, citation) for these instances or any other dataset. |
| Dataset Splits | No | The paper validates against randomly generated instances but does not specify any training, validation, or test splits for these instances. |
| Hardware Specification | No | The paper mentions 'Larger instances made the brute-force calculations too slow' but provides no specific details about the hardware used for running experiments (e.g., CPU/GPU models, memory). |
| Software Dependencies | No | The paper does not specify any software dependencies or their version numbers (e.g., programming languages, libraries, frameworks). |
| Experiment Setup | Yes | We ran the greedy heuristic on each instance 500 times. For each instance, we restarted the search fifty times, and compared the mean utilities to the optimal ones. |