Course Outline

Introduction

Overview of Agent Based Modeling

Case Study: Using Agents to Simulate Financial Transactions

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: Using Agents to Simulate a Pandemic

Choosing a Model Based on the Use Case (Boltzmann Wealth, Schelling Segregation Model, SIR, etc.)

Working with the Mesa's Model and Agent Classes

Defining the Variables

Setting Model Level Parameters

Scheduling the Actions of an Agent

Running the Model

Adding Agents to the Model

Adding Space to the Model

Collecting Data Using the Data Collector

Running the Model Multiple 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

  • Python programming experience
  • Javascript (optional)

Audience

  • Researchers
  • Investigators
  • Analysts
 14 Hours

Testimonials (3)

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