Stability in Online Coalition Formation
Authors: Martin Bullinger, René Romen
JAIR 2025 | Venue PDF | Archive PDF | Plain Text | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Theoretical | We present a comprehensive picture in additively separable hedonic games, leading to dichotomies, where positive results are obtained by deterministic algorithms and negative results even hold for randomized algorithms. |
| Researcher Affiliation | Academia | Martin Bullinger EMAIL Department of Computer Science University of Oxford 7 Parks Road, Oxford OX1 3QD, United Kingdom Ren e Romen EMAIL School of Computation, Information and Technology Technical University of Munich Boltzmannstr 3, 85748 Munich, Germany |
| Pseudocode | Yes | Algorithm 1 Contractually Nash-stable partition of online symmetric { y, x}-ASHGs for y x > 0. Input: Symmetric { y, x}-ASHG Output: Contractually Nash-stable partition π; Algorithm 2 Pareto-optimal partition of online strict ASHG. Input: Strict ASHG Output: Pareto-optimal partition π |
| Open Source Code | No | The paper does not provide any explicit statements about the availability of open-source code for the methodology described. |
| Open Datasets | No | The paper defines and analyzes theoretical models (additively separable hedonic games) and constructs specific game instances for its proofs, rather than using or providing access to empirical datasets. |
| Dataset Splits | No | As the paper primarily focuses on theoretical analysis using constructed game instances rather than empirical datasets, there are no mentions of dataset splits for training, validation, or testing. |
| Hardware Specification | No | The paper does not provide specific details about the hardware used to run experiments, which is consistent with its theoretical nature. |
| Software Dependencies | No | The paper does not list specific software dependencies with version numbers for its methodology, as it focuses on theoretical algorithmic analysis. |
| Experiment Setup | No | The paper does not describe specific experimental setup details such as hyperparameter values, model initialization, or training schedules, as its focus is on theoretical properties of algorithms. |