Innovating Intelligent Systems
Hierarchical Active Inference
Our architecture implements Active Inference within a multi-layer cognitive system where perception, belief updating, and action selection operate under governance constraints. Inference is not an isolated algorithm but part of a structured process regulated by stability monitoring, identity persistence, and temporal phase laws to ensure coherent long-term adaptation.
Generative World Modeling
The system constructs internal generative models that represent hidden causes, physical dynamics, and environmental structure. These models are instantiated through defined representational pipelines and operate within dimensional contracts that ensure consistency across perception, state transitions, and action spaces.
Belief Dynamics Regulation
Learning and inference are modulated by a dedicated belief-dynamics control layer that governs update strength, exploratory drive, and persistence. This ensures adaptive flexibility under change while preventing instability, oscillation, or overconfident belief collapse.
Decision-Making Under Governance
Action selection emerges from policy inference over expected outcomes while remaining subject to identity and structural governance. Decision processes are embedded in a system that separates signal flow from authority flow, ensuring that adaptation occurs within controlled and interpretable boundaries.
Technical White Paper
A detailed architectural description of the Governed Cognitive Architecture for Intelligence (GCAI), covering system layers, inference mechanisms, governance structures, stability control, and operational modes.