The Universal Constraint Engine: Emergent Neuromorphic Architectures from Declarative Constraint Rules
Summary
The article presents the Universal Constraint Engine (UCE), a framework for generating emergent multi-state architectures directly from declarative constraint rules without training. It outlines four layers (Rule Definition, Constraint Solver, Emergent Behavior Engine, Embodiment Mapper) that translate symbolic architectures into hardware across FPGA, neuromorphic, spintronic, and quantum substrates, with examples of simple rule sets producing complex behaviors such as memory and oscillation. A patent-pending approach is contrasted with conventional neural networks, highlighting potential hardware-efficient AI architectures.