Agentpy - Agent-based modeling in Python

Agentpy is an open-source library for the development and analysis of agent-based models in Python. The framework integrates the tasks of model design, numerical experiments, and data analysis within a single environment, and is optimized for interactive computing with IPython and Jupyter. If you have questions or ideas for improvements, please visit the discussion forum or subscribe to the agentpy mailing list.

Quick orientation

• To get started, please take a look at Installation and Overview.

• For a simple demonstration, check out the Wealth transfer tutorial in the Model Library.

• For a detailled description of all classes and functions, refer to API Reference.

• To learn how agentpy compares with other frameworks, take a look at Comparison.

Example

A screenshot of Jupyter Lab with two interactive tutorials from the model library:

Table of contents

• Installation
  • Dependencies
  • Development
• Overview
  • Creating models
  • Using agents
  • Using environments
  • Recording data
  • Running a simulation
  • Multi-run experiments
  • Output and analysis
• User Guide
  • Stochastic processes and reproducibility
• Model Library
  • Wealth transfer
  • Virus spread
  • Flocking behavior
  • Segregation
  • Forest fire
  • Button network
• API Reference
  • Agents
  • Environments
  • Agent-based models
  • Parameter sampling
  • Experiments
  • Output data
  • Analysis
  • Other
• Comparison
  • Agentpy vs. Mesa
• Changelog
  • 0.0.7 (March 2021)
  • 0.0.6 (January 2021)
  • 0.0.5 (December 2020)
  • 0.0.4 (November 2020)
• Contribute
  • Types of contributions
  • How to contribute
  • Pull request guidelines
• About

Indices and tables

• Index

• Search Page