Generalized Notation Notation for Active Inference Models

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Citation KeyFriedman2023GeneralizedNotationNotationActive056

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Overview

Extracted from the local paper documentation when available.

This paper introduces Generalized Notation Notation (GNN), a novel approach to generative model representation that enhances communication and understanding of Active Inference across various domains. GNN serves as a flexible and expressive language for modeling cognitive processes, aiming to facilitate interdisciplinary research and application.

GNNGeneralized Notation Notationmeta-notationsymbolic systemsnotation translationformal representationinteroperability

Use Notes

Concise findings and methods pulled from README/SKILL documentation.

Findings / Concepts

Introduction of Generalized Notation Notation (GNN) for cognitive model representation.
Provision of a Step-by-Step example demonstrating GNN in practice.
Exploration of 'the Triple Play' approach for expressing GNN in linguistic, visual, and executable models.
Bridging gaps among different modeling settings to promote interdisciplinary collaboration.

Methods / Techniques

Development of GNN as a standardized language for describing Active Inference models.
Utilization of ASCII letters and punctuation structured in a Markdown-compliant source file.
Presentation of GNN through examples drawn from existing Active Inference tutorials.
Incorporation of various aspects of language including ontology, morphology, grammar, and pragmatics.

Citation

Plain-text citation for quick reuse.

Friedman, Daniel Ari. 2023. Generalized Notation Notation for Active Inference Models. Zenodo.

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