Manipulation of k-Coalitional Games on Social Networks
Authors: Naftali Waxman, Sarit Kraus, Noam Hazon
IJCAI 2021 | Conference PDF | Archive PDF | Plain Text | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Theoretical | In this paper we study the susceptibility to manipulation of these objectives, given the abilities and information that the manipulator has. Specifically, we show that if the manipulator has very limited information, namely he is only familiar with his immediate neighbours in the network, then a manipulation is almost always impossible. Moreover, if the manipulator is only able to add connections to the social network, then a manipulation is still impossible for some objectives, even if the manipulator has full information on the structure of the network. On the other hand, if the manipulator is able to hide some of his connections, then all objectives are susceptible to manipulation, even if the manipulator has limited information, i.e., when he is familiar with his immediate neighbours and with their neighbours. |
| Researcher Affiliation | Academia | Naftali Waxman1 , Sarit Kraus1 and Noam Hazon2 1Bar-Ilan University, Israel 2Ariel University, Israel {sarit, vaxmann}@cs.biu.ac.il, noamh@ariel.ac.il |
| Pseudocode | No | The paper describes theoretical concepts and proofs but does not include any pseudocode or structured algorithm blocks. |
| Open Source Code | No | The paper does not provide any statement or link indicating that its source code is publicly available. |
| Open Datasets | No | This paper is theoretical and focuses on mathematical proofs and analysis of game theory concepts, rather than empirical evaluation on a dataset. Therefore, it does not mention publicly available datasets for training. |
| Dataset Splits | No | This paper is theoretical and does not involve empirical experiments with dataset splits for training, validation, or testing. |
| Hardware Specification | No | This is a theoretical research paper that does not involve computational experiments, and therefore, no hardware specifications are mentioned. |
| Software Dependencies | No | This is a theoretical research paper focusing on proofs and analysis, and as such, it does not list any software dependencies with specific version numbers for experimental reproducibility. |
| Experiment Setup | No | This is a theoretical research paper that does not involve empirical experiments, and therefore, no experimental setup details, hyperparameters, or training configurations are provided. |