Course Outline
Introduction
Overview of Agent-Based Modelling
Case Study: Using Agents to Simulate Financial Transactions
Overview of Agent-Based Modelling Frameworks for Java, C++, Python, and others
Overview of Mesa's Core Features
Setting Up the Environment
Choosing Between a Text Editor, IDE, or Jupyter Notebook
Creating a Simple Model
Case Study: Using Agents to Simulate a Pandemic
Selecting 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
Visualising the Simulation Interactively
Visualising Agent Activity in a Grid
Adding a Chart to the Visualisation
Creating a Visualisation 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.
