Course Outline
Introduction
Overview of Agent-Based Modeling
Case Study: Simulating Financial Transactions with Agents
Overview of Agent-Based Modeling Frameworks for Java, C++, Python, etc.
Overview of Mesa's Core Features
Setting up the Environment
Choosing between a Text Editor or IDE and Jupyter Notebook
Creating a Simple Model
Case Study: Simulating a Pandemic with Agents
Choosing a Model Based on the Use Case (Boltzmann Wealth, Schelling Segregation Model, SIR, etc.)
Working with Mesa's Model and Agent Classes
Defining Variables
Setting Model-Level Parameters
Scheduling Agent Actions
Running the Model
Adding Agents to the Model
Adding Space to the Model
Collecting Data Using the Data Collector
Running the Model Multiple Times Using the Mesa Batch Runner
Visualizing the Simulation Interactively
Visualizing Agent Activity in a Grid
Adding a Chart to the Visualization
Creating a Visualization Module (optional - requires Javascript)
Integrating the Model with a Machine Learning Application
Best Practices
Troubleshooting
Summary and Conclusion
Requirements
- Experience with Python programming
- Javascript (optional)
Audience
- Researchers
- Investigators
- Analysts
Testimonials (1)
The trainer well prepared the course material beforehand and the session was very flexible and arranged to meet the trainee's interests. The management staffs were also around during the course to help us. The project was well managed in a friendly atmosphere throughout.
