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6 changes: 3 additions & 3 deletions cogant/docs/evaluation/GNN_VALIDATION_REPORT.md
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Expand Up @@ -14,9 +14,9 @@ Date: 2026-06-12

## Spec Source

- Primary: https://github.com/ActiveInferenceInstitute/GeneralizedNotationNotation/blob/main/doc/gnn/gnn_syntax.md
- Type-checker: https://github.com/ActiveInferenceInstitute/GeneralizedNotationNotation/blob/main/src/type_checker/checker.py
- Examples: https://github.com/ActiveInferenceInstitute/GeneralizedNotationNotation/tree/main/input/gnn_files/discrete/
- Primary: https://github.com/ActiveInferenceInstitute/Generalized_Notation_Notation/blob/main/doc/gnn/gnn_syntax.md
- Type-checker: https://github.com/ActiveInferenceInstitute/Generalized_Notation_Notation/blob/main/src/type_checker/checker.py
- Examples: https://github.com/ActiveInferenceInstitute/Generalized_Notation_Notation/tree/main/input/gnn_files/discrete/

## Compliance Check

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2 changes: 1 addition & 1 deletion cogant/examples/demo_server.py
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# Public documentation URL. ``GET /docs`` redirects here when FastAPI's
# built-in OpenAPI UI is not available.
COGANT_DOCS_URL = "https://github.com/ActiveInferenceInstitute/GeneralizedNotationNotation"
COGANT_DOCS_URL = "https://github.com/ActiveInferenceInstitute/Generalized_Notation_Notation"

logger = logging.getLogger("cogant.demo_server")

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2 changes: 1 addition & 1 deletion cogant/py/cogant/__init__.py
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Translates software repositories into Generalized Notation Notation (GNN) — the
Active Inference Institute's structured state-space / process-model notation
(NOT graph neural networks). See
https://github.com/ActiveInferenceInstitute/GeneralizedNotationNotation.
https://github.com/ActiveInferenceInstitute/Generalized_Notation_Notation.

The output of a COGANT run is a GNN-compatible model bundle: hidden states,
observation modalities, actions, policies, transitions, likelihoods,
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2 changes: 1 addition & 1 deletion cogant/py/cogant/schemas/gnn_export.py
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GNNExportBundle: Comprehensive export format for Generalized Notation Notation (GNN).

"GNN" here refers to the Active Inference Institute's Generalized Notation Notation
(https://github.com/ActiveInferenceInstitute/GeneralizedNotationNotation), a structured
(https://github.com/ActiveInferenceInstitute/Generalized_Notation_Notation), a structured
notation for Active Inference state-space and process models — not graph neural networks.

Packages all analysis artifacts (graph structure, semantic mappings, state space,
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2 changes: 1 addition & 1 deletion cogant/pyproject.toml
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Expand Up @@ -64,7 +64,7 @@ analytics = [
"duckdb>=0.9",
]
upstream = [
"generalized-notation-notation @ git+https://github.com/ActiveInferenceInstitute/GeneralizedNotationNotation.git@11a89f0615f1e48ddacca58d1bcf3c5092b1b055",
"generalized-notation-notation @ git+https://github.com/ActiveInferenceInstitute/Generalized_Notation_Notation.git@11a89f0615f1e48ddacca58d1bcf3c5092b1b055",
]
all = [
"pytest>=7.4.0",
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2 changes: 1 addition & 1 deletion cogant/rust/cogant-gnn/src/lib.rs
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@@ -1,7 +1,7 @@
//! GNN export and formatting.
//!
//! "GNN" in COGANT refers to the Active Inference Institute's Generalized
//! Notation Notation (https://github.com/ActiveInferenceInstitute/GeneralizedNotationNotation),
//! Notation Notation (https://github.com/ActiveInferenceInstitute/Generalized_Notation_Notation),
//! a structured notation for Active Inference state-space and process models —
//! NOT graph neural networks. This crate provides functionality for exporting
//! program graphs into that notation.
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2 changes: 1 addition & 1 deletion cogant/tests/unit/test_gnn_spec_compliance.py
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2. Connections section uses bare variable names without parentheses.
3. No duplicate ``## Connections`` header (COGANT extended section renamed).

Spec source: https://github.com/ActiveInferenceInstitute/GeneralizedNotationNotation
Spec source: https://github.com/ActiveInferenceInstitute/Generalized_Notation_Notation
doc/gnn/reference/gnn_syntax.md v2.0.0
Upstream type-checker: src/type_checker/checker.py

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4 changes: 2 additions & 2 deletions cogant/uv.lock

Some generated files are not rendered by default. Learn more about how customized files appear on GitHub.

2 changes: 1 addition & 1 deletion manuscript/01_introduction.md
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Expand Up @@ -6,7 +6,7 @@ The contribution is best read as an **evidence compiler** rather than as a new n

## Terminology: "GNN" in this manuscript

In this manuscript, **GNN** refers to the Active Inference Institute's **Generalized Notation Notation** ([repository](https://github.com/ActiveInferenceInstitute/GeneralizedNotationNotation)) [@friedman2024gnn], a structured notation for state-space and process models---*not* graph neural networks. COGANT translates source code into this notation, producing program-graph and state-space artifacts (state space, observation modalities, actions/policies, likelihood structure, preferences, time settings, parameterization) that downstream tools can consume. Those downstream tools include graph neural network training pipelines, which can ingest the exported tensor views of the program graph, but such neural networks are a *consumer* of COGANT's output, not its output format. Where the manuscript discusses graph neural networks as related work, it uses the phrase "graph neural networks" in full; the acronym GNN always refers to Generalized Notation Notation.
In this manuscript, **GNN** refers to the Active Inference Institute's **Generalized Notation Notation** ([repository](https://github.com/ActiveInferenceInstitute/Generalized_Notation_Notation)) [@friedman2024gnn], a structured notation for state-space and process models---*not* graph neural networks. COGANT translates source code into this notation, producing program-graph and state-space artifacts (state space, observation modalities, actions/policies, likelihood structure, preferences, time settings, parameterization) that downstream tools can consume. Those downstream tools include graph neural network training pipelines, which can ingest the exported tensor views of the program graph, but such neural networks are a *consumer* of COGANT's output, not its output format. Where the manuscript discusses graph neural networks as related work, it uses the phrase "graph neural networks" in full; the acronym GNN always refers to Generalized Notation Notation.

## How to read this document

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2 changes: 1 addition & 1 deletion manuscript/references.bib
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Expand Up @@ -366,7 +366,7 @@ @misc{friedman2024gnn
title = {Generalized Notation Notation (GNN): A structured notation for Active Inference state-space and process models},
author = {{Active Inference Institute}},
year = {2024},
howpublished = {\url{https://github.com/ActiveInferenceInstitute/GeneralizedNotationNotation}},
howpublished = {\url{https://github.com/ActiveInferenceInstitute/Generalized_Notation_Notation}},
note = {Open-source specification and reference implementation; not to be confused with graph neural networks}
}

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