Thesis Project: Agent-Based Model with Dynamic Network

This repository contains code for a thesis project focusing on an agent-based model where agents play games on a dynamic network. The agents' behavior is influenced by factors such as risk aversion and bounded rationality.

Overview

The thesis project aims to simulate interactions among agents in a dynamic network environment. The agents engage in games, and their decisions are influenced by various factors, including risk aversion and bounded rationality. The project explores how these factors impact the behavior and outcomes of agents within the network.

Installation

To run the experiments, follow these steps:

1. Clone this repository to your local machine:

   git clone https://github.com/KarinLeanne/master_thesis.git

2. Navigate to the project directory:

   cd master_thesis

3. Create a conda environment using the provided environment.yml file:

   conda env create -f environment.yml

4. Activate the conda environment:

   conda activate master_thesis

5. Run the main.py script to execute all experiments:

   python main.py

Requirements

• Python (>=3.6)
• Conda

Directory Structure

• data: Contains data generated during simulations.
• docs: Documentation files.
• src: Source code for the agent-based model and experiments.
• utils: Utility functions used in the project.
• environment.yml: Conda environment file specifying dependencies.
• main.py: Main script to run experiments.

License

This project is licensed under the MIT License.

Acknowledgements

We would like to acknowledge the support and guidance provided by Isaak Mengescha during the development of this thesis project.

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