Course Outline
Introduction
Overview of Agent-Based Modelling
Case Study: Simulating Financial Transactions Using Agents
Overview of Agent-Based Modelling 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 Using Agents
Selecting a Model Based on 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 Spatial Elements to the Model
Collecting Data Using the Data Collector
Running the Model Multiple Times Using the Mesa Batch Runner
Interactive Visualisation of the Simulation
Visualising Agent Activity on a Grid
Adding Charts 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)
Target 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.
