Master Thesis - Taming Complexity on Digital Platforms Using Generative AI - An Agent Based Model Approach

Summary

This program is the simulation base of master thesis. An agent based simulation method based on mesa library.

Installation

To install the dependencies use pip and the requirements.txt in this directory. e.g.

    $ pip install -r requirements.txt

How to Run

To run the model single time simulation, run run.py in this directory. It launches a model visualization server

Then open your browser to http://127.0.0.1:8521/ and press Reset, then Run.

To run the batched simulation and generate csv file for analysis, run model.py.

To analysis combined simulations, run combined_simulations.ipynb under code file.

To view sensitivity analysis, run sensitivity analysis.ipynb under code file.

Files

Code File:

• agent.py: Contains the agent class, and the overall agent class.
• model.py: Contains the model class, and the overall model class. This is the most important file to define the parameter of the model, under ''params_ranges'' function.
• server.py: Defines classes for visualizing the model (network layout) in the browser via Mesa's modular server, and instantiates a visualization server.

Plots File:

Contains all the plots for the thesis.

Simulation Data File:

Contains all simulation data generated from model.py.

Further Reading

The mesa library: https://github.com/projectmesa/mesa