Better Strategyproof Mechanisms without Payments or Prior — An Analytic Approach
Authors: Yun Kuen Cheung
IJCAI 2016 | Conference PDF | Archive PDF | Plain Text | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Theoretical | We use an analytic approach to derive strategyproof mechanisms which are more competitive than all prior strategyproof mechanisms. We improve the linear-program-based proof of Guo and Conitzer [2010] to show new upper bounds on competitive ratios. We provide the first compact proof on upper bound of competitiveness. In contrast to most of the prior work, we take on an analytic approach for the problem. |
| Researcher Affiliation | Academia | Yun Kuen Cheung University of Vienna, Faculty of Computer Science, Vienna, Austria yun.kuen.cheung@univie.ac.at |
| Pseudocode | No | The paper describes mathematical mechanisms and proofs but does not include pseudocode or clearly labeled algorithm blocks. |
| Open Source Code | No | The paper does not provide any statement or link regarding the public release of its source code. |
| Open Datasets | No | This theoretical paper focuses on mechanism design and proofs, and as such, does not utilize or refer to publicly available datasets for training, validation, or testing. |
| Dataset Splits | No | The paper is theoretical and does not involve empirical data analysis that would require train/validation/test dataset splits. |
| Hardware Specification | No | The paper is theoretical and does not report on experiments that would require specific hardware for execution. |
| Software Dependencies | No | The paper mentions solving Linear Programs and using 'math software' but does not specify any software names with version numbers. |
| Experiment Setup | No | The paper is theoretical and does not describe empirical experiments requiring details about hyperparameters or system-level training settings. |