Constraint-Emergence Ontology: Reality as Self-Organising Constraint Network

A foundational framework proposing that reality, computation, and engineered systems share structural invariants: constraint networks produce stable patterns (Markov objects) whose boundaries, hierarchies, and dynamics recur across substrates. Spacetime, particles, and gravity are treated as emergent projections of constraint density. Mathematical descriptions are evolved cognitive tools, not the substrate they describe. Meaning is defined as a structural invariant: pattern matched against model, the same operation at every scale. The framework introduces local preorder traversal as a universal computational primitive — the preferred direction function D(x,c) that governs evolution across domains: gradient descent in physics, attention-weighted next-token prediction in LLMs, iterative refinement in software engineering. The Constraint Functor (Part VIII-D) formalizes this cross-domain correspondence via category theory, mapping physical Markov objects to computational Markov objects through structure-preserving functors. A companion paper formalizes LLM computation as constrained topological traversal on a semantic manifold (Emergent Reasoning, https://doi.org/10.5281/zenodo.16592399). Engages with Bohm, Deacon, Friston, Solms, Hawkins, Ladyman & Ross, Wolfram, Penrose, Einstein, Feynman, Deutsch, Smolin, and Rovelli.