# SAL Documentation

Welcome to the Self-Alignment Learning documentation.

## Overview

SAL is a communication-based approach to neural network training that treats optimization as dialogue rather than control.

## Core Principles

- **Ask Before Updating** — Measure stability before modifying parameters
- **Protect What Has Emerged** — Stable patterns represent learned coherence
- **Grow Through Connection** — Learning happens through relationship, not force

## Modules

### [Principles](principles.md)
The philosophy behind SAL and why it matters.

### [Architecture](architecture.md)
Technical deep-dive into SAL's components.

### [How SAL Differs](how_sal_differs.md)
Understanding SAL vs RLHF, Safety training, and Reward-based methods.

### [Visualizations](plots.md)
Visual explanations of SAL concepts.

## Quick Links

- [GitHub Repository](https://github.com/Whiteroom-Ai/sal-learning)
- [Research Paper (Zenodo)](https://zenodo.org/records/17772044)
- [Emergenzwerke Website](https://emergenzwerke.de)

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*SAL: Training as dialogue, not control.*