Unified Cognitive Architecture for Distributed Manifold Reasoning Systems

Inventor(s)

• Donevin frownfelterFollow

Abstract

Donevin Frownfelter (bospaladin34@gmail.com)

This disclosure describes a unified cognitive architecture that integrates three complementary systems—VESPER, NEPHILIM, and the Unified Agent Reasoning Model (UARM)—into a single operational framework for distributed reasoning, semantic computation, and multi‑device intelligence. The architecture introduces a manifold‑based cognitive substrate, enabling agents to perform reasoning as transformations across a non‑Euclidean semantic space rather than through traditional symbolic or statistical pipelines.

The system employs a tensor‑manifold representation for knowledge, a Majorana‑parity logic layer for reversible inference, and a distributed execution mesh that allows heterogeneous devices to participate in a shared cognitive topology. VESPER provides the laminar reasoning core, NEPHILIM extends the architecture with recursive multi‑agent coordination, and UARM defines the formal reasoning grammar that governs semantic flow across the manifold.

This publication covers the architecture, data structures, execution model, and interoperability mechanisms required to implement the system. Applications include distributed AI research tools, multi‑device inference engines, autonomous scientific assistants, and real‑time collaborative reasoning systems. The disclosed framework enables deterministic, interpretable, and extensible cognitive computation without reliance on proprietary black‑box models.

📘 Optional “Description” Section

1. Technical Field

This disclosure relates to distributed artificial intelligence systems, cognitive architectures, and manifold‑based reasoning engines.

2. Background

Conventional AI systems rely on opaque statistical models or symbolic pipelines that do not scale across devices or support interpretable reasoning. There is a need for a deterministic, extensible architecture capable of distributed cognition.

3. Summary

The disclosed system unifies three components—VESPER, NEPHILIM, and UARM—into a single manifold‑based reasoning substrate. The architecture supports reversible logic, tensor‑based semantic flow, and multi‑device execution.

4. System Architecture

- VESPER: Laminar reasoning engine using tensor‑manifold transformations.

- NEPHILIM: Multi‑agent recursive coordination layer.

- UARM: Formal grammar for semantic inference and cognitive topology.

- Distributed Mesh: WebRTC‑based compute fabric enabling shared cognition.

- Manifold Substrate: Non‑Euclidean semantic space with E₈‑derived symmetry.

5. Applications

- Distributed research assistants

- Multi‑device cognitive engines

- Autonomous scientific reasoning

- Deterministic interpretable AI systems.

CLAIMS-

- A unified manifold‑based cognitive architecture — enabling distributed reasoning through geometric transformations in a non‑Euclidean semantic space.

- A tensor‑encoded knowledge representation — mapping cognitive states to continuous, differentiable structures suitable for deterministic inference.

- A laminar reasoning engine (VESPER) — implementing structured semantic flow using layered tensor operations.

- A recursive multi‑agent coordination system (NEPHILIM) — supporting cooperative reasoning, shared state, and emergent problem‑solving across distributed nodes.

- A formal reasoning grammar (UARM) — defining reversible inference rules and manifold‑safe semantic operators.

- A distributed compute mesh — enabling multi‑device cognitive synchronization using peer‑to‑peer communication protocols.

- A Majorana‑parity logic framework — providing reversible, symmetry‑preserving logical transformations for interpretable inference.

- A semantic vector‑field engine — modeling cognition as flow across a manifold‑defined vector field.

- A topology‑aware memory substrate — storing knowledge as stable attractors within a high‑dimensional geometric space.

- A device‑agnostic cognitive interface layer — enabling heterogeneous hardware to participate in a unified reasoning topology.

- A deterministic interpretability mechanism — exposing internal reasoning steps as geometric transformations rather than opaque activations.

- A manifold‑synchronized execution protocol — ensuring semantic consistency across distributed agents without centralized control.

- A modular cognitive‑extension framework — allowing new operators, manifolds, or reasoning modes to be added without retraining.

- A cross‑device semantic continuity method — preserving cognitive state as users transition between devices.

- A reversible inference pipeline — enabling bidirectional reasoning and full traceability of cognitive transformations.

- A manifold‑native debugging and visualization method — allowing developers to inspect tensor curvature, semantic flow, and parity inversions.

- A topology‑driven security model — authenticating agents using geometric invariants rather than credentials.

- A semantic‑resonance optimization technique — improving reasoning stability by tuning phase‑delta alignment across the manifold.

- A unified cognitive topology integrating all components — forming a coherent, interpretable, and extensible distributed intelligence system.

Creative Commons License

This work is licensed under a Creative Commons Attribution 4.0 License.

Recommended Citation

frownfelter, Donevin, "Unified Cognitive Architecture for Distributed Manifold Reasoning Systems", Technical Disclosure Commons, (June 23, 2026)
https://www.tdcommons.org/dpubs_series/10539