Canvas-to-NetLogo Interface Integration

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🧾 Release Note (v0.2-beta)

# Release v0.2-beta — Canvas-to-NetLogo Interface Integration

**Date:** 2025-10-07  
**Author(s):** Jaehu Shim et al.  
**License:** MIT

## Overview
This beta release introduces a new feature for generating complete NetLogo 7.x model interfaces (.nlogox) directly from the ABM Design Canvas.

## Key Additions
- Seed UI Template (`widgets_7.0.nlogox`)
- Interface Builder Script (`build_nlogox_from_canvas.py`)
- Example Interface Output (`Example_Interface_From_Canvas.nlogox`)
- Configuration File (`config.json`)

## Improvements
- Enhanced reproducibility and ease of deployment for ABM prototypes.
- Unified workflow:  
  **Canvas → NLS (model code)** + **Canvas → NLOGOX (interface layout)**

## Next Steps
- Add support for versioned widget templates (7.1, 6.4)
- Introduce automatic BehaviorSpace experiment configuration
- Enable export of `.nlogo` bundle (NLS + NLOGOX + resources)

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ABM Design-to-Code Template (NLS include version)

This release introduces a modular structure using .nls source files and an include-based .nlogo shell model.

ABM Design-to-Code Template v0.1-alpha

🧩 ABM Design-to-Code Template — v0.1-alpha

Initial Public Release (Work-in-Progress)

🌍 Overview

This is the first public release of the ABM Design-to-Code Template —
a lightweight framework that bridges natural-language model design and NetLogo implementation.

It enables researchers, students, and educators to:

• Write ABM designs in plain English using a structured 10-section canvas.
• Convert those descriptions into runnable NetLogo code skeletons with the help of LLMs (e.g., ChatGPT).
• Standardize ABM documentation, replication, and experiment setup through a unified canvas-to-code workflow.

⚠️ This version is an early alpha (v0.1-alpha) and will continue to evolve.

📦 Included Files

File	Description
README.md	Overview, quick start, and design-to-code mapping
LICENSE	MIT open-source license
ABM_Canvas_Template_EN.md	Blank code-oriented ABM design canvas (sections ①–⑩)
Example_Canvas_Filled_EN.md	Entrepreneurship network model example (filled canvas)
Example_Output_Code.nlogo	NetLogo skeleton generated from the example canvas

🧩 Key Features

• Structured ABM Canvas (①–⑩) – covers Research Focus → Agents → Environment → Rules → Interaction → Dynamics → Metrics → Validation → Scenarios → Interpretation.
• Direct mapping to code:
  • ② → breed, own, initialization (setup)
  • ③ → globals, environment setup
  • ④ → behavioral logic (to act)
  • ⑤ → interaction rules (to interact)
  • ⑥ → simulation loop (to go, tick)
  • ⑦ → reporters and outputs
  • ⑧ → validation / experiment routines
  • ⑨ → scenario & policy functions
• Plain-language compatible: design in Markdown or text, then feed directly to ChatGPT / LLM.
• Educational ready: useful for teaching ABM logic and simulation literacy without heavy coding barriers.

🚧 Work-in-Progress (Planned for v0.2–v1.0)

Goal	Description
BehaviorSpace XML examples	Automated multi-run experiment templates
ODD / ODD+D integration	Add a mapping table aligning Canvas sections with ODD protocol items
Additional examples	Policy diffusion, innovation dynamics, social contagion models
Documentation site	GitHub Pages or Notion-based guidebook

🧠 Citation (optional)

Shim, J. (2025). ABM Design-to-Code Template (v0.1-alpha).
GitHub repository: https://github.com/jshim-abm-for-ent/ABM-Design-to-Code-Template

🪪 License

MIT License — free for academic, research, and commercial use with attribution.
See the LICENSE file for full terms.

🔖 Tag & Release Info

• Tag: v0.1-alpha
• Release Title: Initial alpha release — Natural Language → NetLogo ABM workflow
• Branch: main

Commit Message Example:

feat: initial release of ABM Design-to-Code Template (v0.1-alpha)

🤝 Contributions

Feedback and pull requests are warmly welcome!
You can:

• Open an Issue for feature ideas or improvements.
• Submit a Pull Request for bug fixes or added examples.
• Share your own “Canvas + Code” variants in /examples once the repo evolves.

© 2025 J. Shim — ABM Design-to-Code Template
Released under the MIT License.
Empowering researchers to think in models before coding them.