Agentpy - Agent-based modeling in Python

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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

Example

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

Screenshot of Jupyter Lab with two interactive tutorials from the model library

Main features

Aim 1: Intelligent syntax for complex models

  • Custom agent, environment, and network types
  • Easy selection and manipulation of agent groups
  • Support of multiple environments for interaction

Aim 2: Advanced tools for scientific applications

  • Experiments with repeated iterations and parallel processing
  • Parameter sampling and scenario comparison
  • Output data that can be saved, loaded, and re-arranged
  • Sensitivity analysis and (animated) visualizations

Aim 3: Compatibility with established Python libraries

  • Interactive computing with Jupyter/IPython
  • Data analysis with pandas and SALib
  • Network analysis with networkx
  • Visualization with seaborn

Table of contents

Indices and tables