git:20260906.82c8031 to git:20260907.ae194c2

2 added, 2 removed. Audit A to A.

# bnlearn Framework Documentation Agents
## Overview
This document provides agent scaffolding for the bnlearn framework documentation subsystem. The documentation is organized to capture the robust capabilities of the `bnlearn` Python package for use with Bayesian Networks and structural learning.
**Status**: ✅ Documentation
**Version**: 1.0
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## Purpose
Documentation for the `bnlearn` Python package (https://github.com/erdogant/bnlearn) for causal discovery, parameter learning, inference, and sampling methods. It serves as a probabilistic graphical model abstraction layer for causal network generation, inference, and visualization.
## Documentation Organization
The bnlearn Framework documentation system is part of the broader GNN (Generalized Notation Notation) pipeline and ecosystem.
### Related Systems
- - **Main Documentation**: [doc/README.md](../README.md)
+ - **Main Documentation**: [docs/README.md](../README.md)
- **GNN Documentation**: [gnn/AGENTS.md](../gnn/AGENTS.md)
- **Pipeline Reference**: [src/gnn/AGENTS.md](../../src/gnn/AGENTS.md)
- **bnlearn Official Documentation**: [erdogant.github.io/bnlearn](https://erdogant.github.io/bnlearn/)
## Subsystems
- **README.md**: Comprehensive guide, features, pipelines, and code examples for `bnlearn` integration.
**Last Updated**: 2026-04-14
## Quick Navigation
- **Get Started**: See [README.md](README.md)
- **Pipeline Overview**: [src/gnn/AGENTS.md](../../src/gnn/AGENTS.md)
- - **Full Documentation Index**: [doc/README.md](../README.md)
+ - **Full Documentation Index**: [docs/README.md](../README.md)
## Documentation Standards
All documentation in this subsystem follows the professional standards established in the GNN documentation system:
- **Unified**: Directly implements structural, parametric, and causal workflows.
- **Streamlined**: Code snippets directly replicate primary package behaviors.
- **Configurable**: Exposes metrics and methods (e.g., HC, EX, bic, k2).
- **Functional**: End-to-end functionality including synthetic data and continuous discretization.
- **Logged Tested Documented**: Conforms to the standard repository-wide validation schema.
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**Status**: ✅ Production Ready
**Compliance**: Professional documentation standards
**Maintenance**: Regular updates with new features