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ABM-Canvas-Toolkit

A structured and practical toolkit for designing Agent-Based Models (ABMs) using a clear, reproducible, and research-oriented ABM Canvas framework.
This repository provides ABM Canvas 2.0, example templates, and optional scripts for converting structured design specifications into NetLogo model components.


🚀 Overview

Agent-Based Modeling (ABM) often requires translating conceptual model designs into executable code while maintaining clarity, reproducibility, and transparency.
ABM Canvas Toolkit helps streamline this process by providing:

  • A formalized ABM Canvas (version 2.0)
  • Example templates for design documentation
  • A clean directory structure for organizing models
  • (Optional) Scripts for generating NetLogo .nls and .nlogox files from Canvas text
  • A foundation for ABM education, research, and collaborative modeling projects

🧩 ABM Canvas 2.0

ABM Canvas 2.0 is a structured design template that organizes essential ABM components into clear sections, enabling reproducible documentation and consistent model development.

Canvas 2.0 consists of 10 major sections:

  1. Research question & simulation purpose
  2. Agent breeds & attributes
  3. Environment & constraints
  4. Process overview & scheduling
  5. Behavioral rules
  6. Interaction rules
  7. Initialization (setup)
  8. Parameters (sliders, switches, globals)
  9. Evaluation metrics (plots, monitors, logging)
  10. Experiment design (manual scenarios + BehaviorSpace)

📄 The full template is available at:
/templates/ABM_Canvas_2.0.md


🎓 Use Cases

✔ Research

Use the Canvas to document model mechanisms for papers, supplementary materials, or replication packages.

✔ Education

Students can design ABMs without immediately writing code — Canvas acts as a conceptual bridge between idea and implementation.

✔ Collaboration

Common structure promotes alignment between researchers, developers, and domain experts.


📝 License

This project is released under the MIT License, allowing wide reuse in research and teaching.


🙌 Contributions

Contributions are welcome — feel free to submit issues, improvements, or pull requests.
If you are using the toolkit for research or education, sharing your examples would be especially helpful.

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Natural-language ABM design canvas for executable NetLogo code generation using AI

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