Notice: The reproducibility variables underlying each score are classified using an automated LLM-based pipeline, validated against a manually labeled dataset. LLM-based classification introduces uncertainty and potential bias; scores should be interpreted as estimates. Full accuracy metrics and methodology are described in [1].
Incentives for Strategic Behavior in Fisher Market Games
Authors: Ning Chen, Xiaotie Deng, Bo Tang, Hongyang Zhang
AAAI 2016 | Venue PDF | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Theoretical | In this paper, we quantitatively measure a buyer s utility gain by strategic plays by adopting the notion of incentive ratio (Chen, Deng, and Zhang 2011). Incentive ratio is deο¬ned as the factor of the largest possible utility gain that a participant can achieve by behaving strategically, given that all other participants have their strategies unchanged. We show that incentive ratio is at most 2 if all buyers have WGS utility functions. |
| Researcher Affiliation | Academia | Ning Chen Division of Mathematical Sciences Nanyang Technological University Singapore, Xiaotie Deng Department of Computer Science Shanghai Jiao Tong University Shanghai, China, Bo Tang Department of Computer Science University of Oxford, UK, Hongyang Zhang Department of Computer Science Stanford University, USA |
| Pseudocode | No | The paper does not contain any structured pseudocode or algorithm blocks. |
| Open Source Code | No | The paper does not provide any statement or link regarding the release of source code for the methodology described. |
| Open Datasets | No | The paper is theoretical and does not use or describe any datasets for training or evaluation. |
| Dataset Splits | No | The paper is theoretical and does not involve empirical experiments requiring dataset splits. |
| Hardware Specification | No | The paper is theoretical and does not mention any specific hardware used for experiments or analysis. |
| Software Dependencies | No | The paper is theoretical and does not list any specific software dependencies with version numbers. |
| Experiment Setup | No | The paper is theoretical and does not describe an experimental setup with hyperparameters or system-level training settings. |