Helipad: A Framework for Agent-Based Modeling in Python
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...
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| Vydané v: | Journal of open research software Ročník 13 |
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| Hlavný autor: | |
| Médium: | Journal Article |
| Jazyk: | English |
| Vydavateľské údaje: |
Ubiquity Press Ltd
05.11.2025
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| Predmet: | |
| ISSN: | 2049-9647, 2049-9647 |
| On-line prístup: | Získať plný text |
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| Shrnutí: | 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, Spatial modeling, Research software, Simulation software |
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| ISSN: | 2049-9647 2049-9647 |
| DOI: | 10.5334/jors.547 |