Fair Information Sharing for Treasure Hunting
Authors: Yiling Chen, Kobbi Nissim, Bo Waggoner
AAAI 2015 | Conference PDF | Archive PDF | Plain Text | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Theoretical | We design contract-based mechanisms for information sharing without money. ... We construct a one-shot contract-based mechanism and show that in this mechanism, to maximize winning probability, each agent should report her private information truthfully if all other agents report truthfully. Then, we prove the fairness and welfare properties of the mechanism. We also show that the mechanism satisfies ϵ-voluntary participation for ϵ 0 as information sets grow large. |
| Researcher Affiliation | Academia | Yiling Chen Harvard SEAS yiling@seas.harvard.edu Kobbi Nissim Ben-Gurion University and Harvard CRCS kobbi@cs.bgu.ac.il Bo Waggoner Harvard SEAS bwaggoner@fas.harvard.edu |
| Pseudocode | Yes | Mechanism 1: One-Shot Mechanism Input: Si for each agent i. Output: A partition of SN = i NSi, with Πi assigned to agent i. set SN = i Si; foreach agent i do compute i s winning probability pi; end initialize each Πi = ; foreach location s SN do let i be a random agent chosen with probability pi; add s to Πi; end output the sets Πi for each i; |
| Open Source Code | No | The paper does not provide concrete access to source code for the methodology described. |
| Open Datasets | No | The paper is theoretical and does not use or reference any datasets for training or evaluation. |
| Dataset Splits | No | The paper is theoretical and does not describe or use data splits for validation. |
| Hardware Specification | No | The paper is theoretical and does not describe computational experiments or specific hardware used. |
| Software Dependencies | No | The paper is theoretical and does not list specific software dependencies with version numbers. |
| Experiment Setup | No | The paper is theoretical and does not provide details about an experimental setup, hyperparameters, or training settings. |