Learning Hedonic Games
Authors: Jakub Sliwinski, Yair Zick
IJCAI 2017 | Conference PDF | Archive PDF | Plain Text | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Theoretical | We lay the theoretical foundations for studying the interplay between two fundamental concepts: coalitional stability, and PAC learning in hedonic games. We introduce the notion of PAC stability the equivalent of core stability under uncertainty and examine the PAC stabilizability and learnability of several popular classes of hedonic games. |
| Researcher Affiliation | Academia | Jakub Sliwinski and Yair Zick National University of Singapore dcsjaku,dcsyaz@nus.edu.sg |
| Pseudocode | Yes | Algorithm 1 An algorithm finding a PAC stable outcome for Top Responsive games |
| Open Source Code | No | No explicit statement or link is provided for the open-sourcing of the methodology's code. |
| Open Datasets | No | The paper is theoretical and does not describe experiments using a specific dataset or provide access information for one. It refers to 'm samples' as a theoretical input to the PAC learning model, not as an actual empirical dataset. |
| Dataset Splits | No | The paper is theoretical and does not describe an experimental setup with dataset splits (train/validation/test) as it focuses on theoretical proofs and analyses. |
| Hardware Specification | No | The paper is theoretical and does not describe any computational experiments that would require specific hardware specifications. |
| Software Dependencies | No | The paper is theoretical and does not describe any implementation details that would require specific software dependencies with version numbers. |
| Experiment Setup | No | The paper is theoretical and does not provide specific experimental setup details such as hyperparameters or training configurations. Algorithm 1 is a theoretical description, not a practical setup for experiments. |