Generalized Notation Notation (GNN) is a text-based notation project for communicating and specifying generative models. It provides a shared language for describing Active Inference and related models in a way that is both human-readable and machine-processable, enabling interoperability across tools and codebases.
Overview
GNN defines a notation system for generative models used in Active Inference and related frameworks. By standardizing how models are described, GNN enables clearer communication between researchers, easier translation between implementations, and more robust tooling around model specification and analysis.
Publication
GNN was originally published as Smékal and Friedman (2023) in the Active Inference Journal, archived openly on Zenodo.
Status and Resources
GNN has an active repository and has been used across several Institute projects. Documentation and examples are available through the repository.
Participate
Contributions include specification work, tooling development, documentation, and applying GNN to new modeling domains. Background in formal modeling or Active Inference is helpful.