χONN · Hub

Ontology Neural Network.

ONN learns a latent state carrying explicit ontology structure; ORTSF closes the loop with delay-robust control on top of that topology. This hub collects the working definitions, the mathematical commitments, and every manuscript in the thread.

Suggested reading order

01Track overview
02ONN + ORTSF framework paper
03Integrated architecture
04Extensions & theorems as needed

Track overview

The high-level research-track page — what ONN is, why it matters, and where it sits in the broader programme.

updated 16 Apr 2026
Ontology Neural Networks
A learning architecture whose latent state carries the explicit type structure of a target ontology, enabling cohomological analysis of learned features and delay-robust embodied control through the companion ORTSF framework.

Canonical specifications

The authoritative formal statement of the ONN architecture and the ORTSF operator family.

ONN
ONN Canonical Specification
The authoritative formal specification of the Ontology Neural Network architecture — primitives, the constraint-satisfaction formalism, the topology-preservation guarantee, and the interface to ORTSF delay-robust control.

Research roadmap & status

Dated notes tracking what is settled, what is under active development, and the open problems on the critical path.

updated 18 Feb 2026
ONN — Current State and Theory Snapshot
A snapshot of Ontology Neural Network theory and implementation as it stands — what is rigorously proved, what is empirically validated, and what remains open.

Integration & north-star

ONN as one half of the unified cognitive-reasoning architecture. The integrated-architecture note sits in Part 0 because it binds SCC and ONN together.

Part 0 · north-star
Integrated Architecture — SCC × ONN as one cognitive-reasoning system
The ultimate design target of the whole research programme: a single cognitive-reasoning architecture that unifies Soft Cognitive Cohesion (SCC) and Ontology Neural Networks (ONN). Four layers, one pipeline, one vision.

Mathematical results

Theorems and proofs specific to ONN — topology preservation, cohomological stability, and the delay-robust feedback bound. Individual proof pages will appear here as they are written.

Draft
ONN · mathematical results
Individual theorem pages will appear here as proofs are formalised.

Essays & working notes

Exploratory documents, working notes, and essay-form writing in the ONN thread.

ONN
ONN vs Transformer — Experiment Plan
The full experimental protocol comparing ONN to Transformer baselines under matched compute and delay regimes.

Manuscripts

Every ONN-track paper — published, accepted, or in preprint.

← Track overview SCC hub →Integrated architecture →

Ontology Neural Network.

Ontology Neural Networks

ONN Canonical Specification

ONN — Current State and Theory Snapshot

Integrated Architecture — SCC × ONN as one cognitive-reasoning system

ONN · mathematical results

ONN vs Transformer — Experiment Plan

Ontology Neural Network and ORTSF: A Framework for Topological Reasoning and Delay-Robust Control

Advanced Topology-Preserving Neural Networks: An Extension of ONN/ORTSF Framework with Dynamic Structural Optimization

Constructive Lyapunov Functions via Topology-Preserving Neural Networks

Ontology Neural Networks for Topologically Conditioned Constraint Satisfaction

Ontology Neural Network.

Ontology Neural Networks

ONN Canonical Specification

ONN — Current State and Theory Snapshot

Integrated Architecture — SCC × ONN as one cognitive-reasoning system

ONN · mathematical results

ONN vs Transformer — Experiment Plan

Ontology Neural Network and ORTSF: A Framework for Topological Reasoning and Delay-Robust Control

Advanced Topology-Preserving Neural Networks: An Extension of ONN/ORTSF Framework with Dynamic Structural Optimization

Constructive Lyapunov Functions via Topology-Preserving Neural Networks

Ontology Neural Networks for Topologically Conditioned Constraint Satisfaction