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 [1].
Stable and Envy-free Partitions in Hedonic Games
Authors: Nathanaël Barrot, Makoto Yokoo
IJCAI 2019 | Venue PDF | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Theoretical | We first show that... an individually stable and justified envy-free partition may not exist and deciding its existence is NPcomplete. Then, we prove that the top responsiveness property guarantees the existence of a Pareto optimal, individually stable, and envy-free partition, but it is not sufficient for the conjunction of core stability and envy-freeness. Finally, under bottom responsiveness, we show that deciding the existence of an individually stable and envy-free partition is NP-complete, but a Pareto optimal and justified envy-free partition always exists. |
| Researcher Affiliation | Academia | Nathana el Barrot1,2 and Makoto Yokoo2,1 1Riken, AIP Center 2Kyushu University |
| Pseudocode | Yes | Algorithm 1 Extended Top Covering Algorithm |
| Open Source Code | No | The paper does not provide any specific link or explicit statement about releasing source code for the methodology described. |
| Open Datasets | No | The paper is theoretical and uses abstract examples for proofs, rather than empirical datasets with access information. |
| Dataset Splits | No | The paper describes theoretical results and does not mention training, validation, or test dataset splits. |
| Hardware Specification | No | The paper is theoretical and does not describe computational experiments requiring specific hardware specifications. |
| Software Dependencies | No | The paper is theoretical and does not mention specific software dependencies or their version numbers. |
| Experiment Setup | No | The paper is theoretical and does not describe an experimental setup with hyperparameters or system-level training settings. |