Geospatial researchers, data scientists, and modelers interested in spatial Active Inference applications.

GEO-INFER

Geospatial modeling using Active Inference and spatial data analysis techniques.

Lead: Daniel Friedman

GEO-INFER develops geospatial modeling methods grounded in Active Inference. The project integrates spatial data analysis with the Active Inference framework, opening applications in ecology, urban planning, resource management, and other domains where geographic context matters.

Overview

GEO-INFER combines geospatial analysis methods — including raster data, spatial statistics, and geographic information systems — with Active Inference principles. The project explores how agents operating in spatially structured environments can be modeled and understood through the free energy framework. It is organized as a modular ecosystem with components spanning math and inference, geospatial-temporal infrastructure, domain modules (such as agriculture, health, economics, risk, and logistics), operations and security (including a dedicated security and privacy framework), and higher-level application, simulation, and governance layers, all linked through an explicit module dependency graph.

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Public GitHub organization for Institute repositories and open-source work.

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GEO-INFER repository

Audience: Developer

Geospatial modeling repository connected to ecological and bioregional applications.

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Repository / Projects

GEO-INFER

Audience: Developer

Geospatial Active Inference and ecological/bioregional modeling work.

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