Fisher Markets with Social Influence

Authors: Jiayi Zhao, Denizalp Goktas, Amy Greenwald

AAAI 2023 | Conference PDF | Archive PDF | Plain Text | LLM Run Details

Reproducibility Variable Result LLM Response
Research Type Experimental Finally, we derive a novel first-order method that solves this Stackelberg system in polynomial time, prove that it is equivalent to computing competitive equilibrium prices via tˆatonnement, and run experiments that confirm our theoretical results.
Researcher Affiliation Academia 1 Department of Computer Science, Pomona College 2 Department of Computer Science, Brown University
Pseudocode Yes Algorithm 1: NE-Oracle Tˆatonnement For Influence Fisher Markets
Open Source Code No The paper does not provide any links to open-source code or explicit statements about code availability.
Open Datasets No The paper describes using randomly initialized linear, Cobb-Douglas, and Leontief Fisher markets for experiments, but does not refer to a specific publicly available dataset with concrete access information like a link or citation.
Dataset Splits No The paper does not provide specific training/validation/test dataset splits. It mentions running experiments on 'randomly initialized linear, Cobb-Douglas, and Leontief Fisher markets' but gives no details on data partitioning.
Hardware Specification No The paper does not provide specific hardware details (e.g., GPU/CPU models, memory) used for running its experiments.
Software Dependencies No The paper does not provide specific ancillary software details with version numbers (e.g., library or solver names with version numbers) needed to replicate the experiment.
Experiment Setup No The paper describes the types of utility functions (linear, Cobb-Douglas, Leontief) used in the experiments and mentions 'randomly initialized' markets, but does not specify concrete hyperparameters (e.g., learning rate, batch size, epochs) or other system-level training configurations.