Incentive-Compatible Selection for One or Two Influentials
Authors: Yuxin Zhao, Yao Zhang, Dengji Zhao
IJCAI 2023 | Conference PDF | Archive PDF | Plain Text | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Theoretical | In this paper, we first design a mechanism to actually reach the bound. Then, we move this forward to choosing two agents and propose a mechanism to achieve an approximation ratio of (3 + ln 2)/(4(1 + ln 2)) ( 0.54). Then, we show the mechanism is IC when β 1/2. Theorem 1. A β-logarithmic mechanism is IC if β 1/2. Theorem 8. LALD is 3+ln 2 4(1+ln 2)-optimal. |
| Researcher Affiliation | Academia | Yuxin Zhao , Yao Zhang and Dengji Zhao Shanghai Tech University {zhaoyx5, zhangyao1, zhaodj}@shanghaitech.edu.cn |
| Pseudocode | Yes | β-logarithmic Mechanism (β-LM) 1. Given a network G = (N, E), find the 1-influential set Sinf. 1 (G) = {i1, . . . , im}, where it it+1 for all 1 t < m. 2. Assign the probability of each agent to be selected as follows: |
| Open Source Code | No | No mention of open-source code or links to repositories for the described methodology. |
| Open Datasets | No | This is a theoretical paper that does not use datasets for training or evaluation. |
| Dataset Splits | No | This is a theoretical paper that does not involve validation datasets. |
| Hardware Specification | No | This is a theoretical paper that does not discuss hardware specifications for experiments. |
| Software Dependencies | No | This is a theoretical paper that does not list software dependencies with version numbers. |
| Experiment Setup | No | This is a theoretical paper that does not describe an experimental setup or hyperparameters. |