Incentives for Strategic Behavior in Fisher Market Games

Authors: Ning Chen, Xiaotie Deng, Bo Tang, Hongyang Zhang

AAAI 2016 | Conference PDF | Archive PDF | Plain Text | 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 defined 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.