Truthful Interval Covering
Authors: Argyrios Deligkas, Aris Filos-Ratsikas, Alexandros A. Voudouris
IJCAI 2024 | Conference PDF | Archive PDF | Plain Text | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Theoretical | We initiate the study of a novel problem in mechanism design without money, which we term Truthful Interval Covering (TIC)... Our goal is to design truthful mechanisms to prevent such strategic misreports and achieve good approximations to the best possible social or egalitarian cost. We consider the fundamental setting of known intervals with equal lengths and provide tight bounds on the approximation ratios achieved by truthful deterministic mechanisms. For the social cost, we also design a randomized truthful mechanism that outperforms all possible deterministic ones. |
| Researcher Affiliation | Academia | 1Royal Holloway University of London, UK 2University of Edinburgh, UK 3University of Essex, UK |
| Pseudocode | No | The paper describes mechanisms (e.g., MEDIAN mechanism, UNIFORM-STATISTIC) conceptually and proves their properties, but it does not present them in formal pseudocode or algorithm blocks. |
| Open Source Code | No | The paper is theoretical and focuses on proofs and mechanism design. There is no mention or indication of providing open-source code for the described methodologies. |
| Open Datasets | No | The paper is theoretical and does not use or refer to any datasets for training or evaluation. The instances like WCI1 and WCI2 are conceptual worst-case instances for theoretical analysis, not actual datasets. |
| Dataset Splits | No | The paper is theoretical and does not involve empirical validation on datasets, thus no dataset splits (training, validation, test) are specified. |
| Hardware Specification | No | The paper is theoretical and does not describe any experiments that would require specific hardware for execution. |
| Software Dependencies | No | The paper is theoretical and does not describe any software implementation or dependencies with version numbers. |
| Experiment Setup | No | The paper is theoretical and does not involve empirical experiments, thus no experimental setup details like hyperparameters or training configurations are provided. |