HermiTech-LLC / Glue

GLUE, standing for Genetic Language for Unsupervised Evolution, is a unique, device-hosted runtime aimed at autonomously evolving robotic intelligence. It integrates genetic algorithms with deep learning, offering a toolkit for independent AI development in robotics.

GLUE: A Multi-Paradigmal, Device Hosted Language & Runtime for Advanced Robotics

Introduction

GLUE (Genetic Language for Unsupervised Evolution) is an innovative language framework, combining Rust and Python's robust features to create a multi-paradigm, device-hosted environment. It is designed for advanced robotics applications, integrating historical and contemporary elements like Norse runes and Hehner's Unified Algebra notation for expressive and powerful computation in unsupervised evolutionary robotics.

Syntax Fusion

GLUE’s syntax is a unique blend:

• Runes & Glyphs: Ancient symbols for compact, expressive commands, ideal for complex robotic systems.
• Hehner's Algebra Notation: Mathematical precision in computational logic.

Planned Integration with JavaScript

To enhance GLUE's capabilities, we plan to integrate JavaScript's event-driven architecture, contributing to a richer, more versatile language platform.

IDE & Docs

keep your eye Here

Enhanced Core Components

Language Design

• Synthesis of Paradigms: Merging Python's readability, Rust's efficiency, and JavaScript's asynchronous patterns for a robust language design.
• Type System and Memory Management: Rust's static typing and memory safety, combined with Python's dynamic nature, provide a balance of performance and developer-friendliness.

Compiler/Interpreter Evolution

• Compiler Upgrades: Leveraging Rust's regex and parser combinators for robust syntax parsing. The AST generation will be fortified by Rust’s strong typing.
• Runtime Enhancements: Incorporating JavaScript's JIT compilation strategies alongside Rust's AOT model, catering to diverse computational requirements.

Runtime Environment

• Interoperability and Memory Management: Bridging Python, Rust, and JavaScript libraries through FFIs, while adopting Rust's ownership model for efficient memory management.
• Expanded Standard Library: Emphasizing AI and robotics, integrating Rust's performance-oriented features with Python's rapid development capabilities.

Development Ecosystem

• Tooling: Establishing a package manager inspired by cargo and npm. Creating robust testing and debugging tools that reflect the best practices of all three languages.
• Community and Documentation: A commitment to thorough documentation and active community engagement, inviting contributions and discussions for continual improvement.

Contribute and engage in discussions here

Illustrative GLUE Code Example

𓃀 Pathfinding.glue

𓊪 PathOps {
  𓃀 Generate Grid Rune
  𓁹 GenerateGrid = () => {
    𓃀 Grid generation logic
  }

  𓃀 Find Path Rune
  𓂅 FindPath = (𓂆 Grid, 𓂇 Start, 𓂈 End) => {
    𓃀 Pathfinding logic
  }
}

𓂉#202 = PathOps

𓂊 𓂉#202 as 𓂋 PO

𓂌 Grid = 𓂋 PO.𓁹()
𓂍 Start = [0, 0]
𓂎 End = [5, 5]
𓂏 Path = 𓂋 PO.𓂅(𓂌 Grid, 𓂍 Start, 𓂎 End)

𓂒("Path: " ⊕ 𓂏 Path)

Moving Forward

We invite the community of developers, roboticists, and enthusiasts to engage with GLUE, contributing to the evolution of autonomous robotics. The integration of Python, Rust, and JavaScript functionalities will propel GLUE to new heights, fostering innovation in the realm of robotic applications.