🚀 Initial Release — v1.0.0

This is the first official release of Transformer Grid Neuro, a Python-based research package implementing a neuro-inspired 3×3 transformer-like grid system for simulating local information propagation, neuronal connectivity patterns, and downstream robotic-control mapping.

📦 Included in This Release

Core Modules

• grid_node.py — Defines the computational node structure and update rules
• grid_system.py — Implements the 3×3 grid topology with neighbor-based propagation
• robot_transfer.py — Demonstrates mapping of processed grid states to robotics control signals
• main.py — Execution script for running propagation cycles and observing system behavior

Project Structure

• src/ — Python package with all core modules
• paper/ — Includes the theoretical PDF (Neuronal_Connectivity.pdf)
• README.md — Full documentation and usage instructions
• LICENSE — MIT License

🧠 Highlights

• Neuro-inspired transformer grid architecture
• Weighted neighbor-state propagation model
• Configurable state dimensions and update cycles
• Modular, extendable Python structure
• Robotics integration sample for downstream application

📥 Getting Started

git clone https://github.com/<your-username>/transformer-grid-neuro
cd transformer-grid-neuro
python3 src/main.py

📘 Citation

A Zenodo DOI will be generated automatically for this release. Please cite this version when referencing the project in research.