Agent-based modeling was an unfilled niche in Python’s robust and growing scientific computing ecosystem, until Mesa was created. Mesa allows users to quickly create agent-based models using built-in core components (such as agent schedulers and networks) or customized implementations; visualize them using an innovative browser-based interface; and analyze their results using Python’s extensive data analysis tools. Mesa is being developed by a group of modeling practitioners with experience in academia, government, and the private sector. It is also completely open-source, encouraging users to contribute to what we hope will be a growing repository of model components which others can reuse and expand upon in future research.

In this talk, you will learn the following... What are agent-based models & why should I care? (An overview of various agent-based models, the existing software ecosystem, and practical applications) What is Mesa? (An overview of Mesa’s features / components and architecture.) * How do I a build a model using Mesa? (A walkthrough of how to write a model.)