ActiveInferenceInstitute

Python implementation of Active Inference with belief updating, free energy minimization, and policy selection

Ada implementation of Active Inference with belief updating, free energy minimization, and policy selection

Assembly implementation of Active Inference with belief updating, free energy minimization, and policy selection

Brainfuck implementation of Active Inference with belief updating, free energy minimization, and policy selection

C implementation of Active Inference with belief updating, free energy minimization, and policy selection

Clojure implementation of Active Inference with belief updating, free energy minimization, and policy selection

COBOL implementation of Active Inference with belief updating, free energy minimization, and policy selection

Common Lisp implementation of Active Inference with belief updating, free energy minimization, and policy selection

Geospatial Active Inference framework with 44 modules for ecological, civic, and commercial spatial analysis. Use when working with geospatial data, Active Inference, Bayesian modeling, H3 hexagonal indexing, spatial statistics, or any domain-specific…

Place-based analysis with H3 hexagonal indexing. Use when performing place identification, catchment area analysis, county/region geometry loading, or H3-based place-shedding and geographic boundary operations.

Unified test runner and testing infrastructure for the GEO-INFER ecosystem. Use when running cross-module tests, configuring test categories, setting up test fixtures for spatial data, or analyzing test results.

Geospatial risk modeling including catastrophe models, exposure analysis, and underwriting. Use when assessing spatial risk, building catastrophe models, analyzing exposure/hazard/vulnerability, or computing portfolio risk metrics.

Canonical GEO-INFER Active Inference implementation. Use when implementing or reviewing free-energy minimization, belief updating, generative models, policy selection, H3/spatial active inference, or typed ACT diagnostics.

Bayesian inference and probabilistic modeling for geospatial data. Use when building hierarchical models, computing posteriors with PyMC or TFP, performing variational inference, model comparison (LOO/WAIC/DIC), or spatial Gaussian processes.

Climate modeling and environmental analysis. Use when analyzing climate data, projecting future climate scenarios (RCP/SSP), computing climate indices (SPI, PDSI), performing statistical downscaling, or assessing climate change impacts on geographic regions.

Educational technology for geospatial learning. Use when creating spatial analysis curricula, interactive GIS exercises, learning progression models, competency assessment for geographic concepts, or step-by-step spatial tutorials.

Generalized Notation Notation (GNN) processing pipeline for Active Inference generative models. Use when working with GNN files, running the 25-step pipeline, parsing model specifications, generating simulations, or producing visualizations and reports from…

GNN comprehensive test suite execution and management. Use when running tests, writing new test cases, checking coverage, debugging test failures, or validating pipeline correctness across all 25 GNN modules.

GNN graph and matrix visualization generation. Use when creating network graph plots, matrix heatmaps, state space diagrams, or other visual representations of GNN models.

GNN advanced statistical analysis and result aggregation. Use when performing statistical analysis on simulation results, cross-simulation aggregation, computing information-theoretic metrics, or creating analytical visualizations of pipeline outputs.

GNN audio generation and sonification. Use when creating audio representations of GNN models, generating sonification of state spaces, or working with SAPF and Pedalboard audio backends.

GNN file discovery, parsing, and multi-format serialization. Use when reading GNN model files, parsing StateSpaceBlock definitions, extracting connections, validating GNN syntax, or converting between GNN formats.

GNN interactive GUI for constructing and editing GNN models. Use when building visual model editors, launching the GNN GUI application, or working with the multi-panel GUI system (gui_1, gui_2, gui_3, oxdraw).

GNN Active Inference ontology processing and validation. Use when working with ActInfOntologyAnnotation sections, mapping GNN variables to ontology terms, validating semantic annotations, or exploring Active Inference concept hierarchies.

Core inference logic, prompt construction, and RDF/Nanopublication serialization.

Tooling for injecting JSON/CSV statistics into Markdown evaluation templates.

Core orchestration guidelines and MCP interactions for the src/ library.

Orchestration for bibliometrics, topological network analysis, and hypothesis scoring.

Orchestrates matplotlib and seaborn pipelines for rendering figures.

Operations for federated API querying across OpenAlex, Semantic Scholar, and arXiv.

Master Cohere v2 Chat API with Python, specializing in entity extraction using JSON Schema mode for structured outputs. Use when extracting entities from text, building data extraction pipelines, implementing NER systems, or requiring validated JSON responses…

Master SurrealDB 2.3.x with Python for multi-model database operations including CRUD, graph relationships, vector search, and real-time queries. Use when working with SurrealDB databases, implementing graph traversal, semantic search with embeddings, or…

AI agent skill for the Active Inference Institute courses repository. Covers course content, the Python publishing engine, and CI/test infrastructure.

Work on the Active Inference Institute public website (institute_website): a static, zero-dependency Node build that renders JSON content into clean-URL HTML for GitHub Pages, with a strict CSP + link + public-safety contract. USE WHEN adding or editing a…

START — Scalable, Tailored Active-inference Research & Training. An AI-powered system for creating personalized Active Inference and FEP curricula. Pipeline: research (Perplexity) → curriculum generation (OpenRouter) → visualization → translation.