Helipad: A Framework for Agent-Based Modeling in Python

15 Pages Posted: 30 Jun 2021

Date Written: June 19, 2021

Abstract

Agent-based modeling tools commonly trade off usability against power and vice versa. On the one hand, full development environments like NetLogo feature a shallow learning curve, but have a relatively limited proprietary language. Others written in Python or Matlab, for example, have the advantage of a full-featured language with a robust community of third-party libraries, but are typically more skeletal and require more setup and boilerplate in order to write a model. Helipad is introduced to fill this gap. Helipad is a new agent-based modeling framework for Python with the goal of a shallow learning curve, extensive flexibility, minimal boilerplate, and powerful yet easy to set up visualization, in a full Python environment. We summarize Helipad’s general architecture and capabilities, and briefly preview a variety of models from a variety of disciplines, including multilevel models, matching models, network models, spatial models, and others.

Keywords: Agent-based modeling, Computational social science

JEL Classification: C63

Suggested Citation

Harwick, Cameron, Helipad: A Framework for Agent-Based Modeling in Python (June 19, 2021). Available at SSRN: https://ssrn.com/abstract=3870501 or http://dx.doi.org/10.2139/ssrn.3870501

Cameron Harwick (Contact Author)

SUNY College at Brockport ( email )

Brockport, NY 14420
United States

HOME PAGE: http://cameronharwick.com

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