A 119-Module Neurosymbolic Cognitive Architecture Blueprint 119 Modules Simulated Thought, Symbolic Memory Reflective Processes Version with Tool Mapping and Buildability Notes
A 119-Module Neurosymbolic Cognitive Architecture Framework
Theoretical Design, Module Specifications, and Practical Tool Mapping (2026)
This document presents a conceptual neurosymbolic cognitive architecture consisting of 119 modules. The framework integrates symbolic reasoning, latent representations, visual simulation, reflective processes, memory composability, safety mechanisms, perception, autonomy, self-improvement, and multi-agent coordination.
Purpose and Scope
The design is intended for theoretical exploration, academic research, and human-guided sandbox simulation only. It is not intended for autonomous deployment or operational use in real-world systems.
Key features include:
Explicit symbolic memory and pegging mechanisms
Low-resolution visual thought substrate for grounding
Perpetual reflection and meta-cognition loops
Layered safety, alignment, and ethical controls
Bridging between symbolic and latent representations
Tool mapping to 2026-era libraries and frameworks
Module Structure
The architecture is organized into 119 modules grouped as follows:
Core human-like modules (1–42)
Advanced lab-inspired modules (43–90)
Collaboration and culture modules (91–99)
Symbolic-latent hybrid bridges (100–101)
Extended autonomy and persistence modules (102–109)
Deployment, robustness, and maturity modules (110–118)
Implicit-to-visible projection and self-observation layer (119)
Practical Implementation Notes
A dedicated section maps the modules to realistic 2026 tools (e.g., LangGraph, Neo4j, VQ-VAE, DeepProbLog, Brian2, KONA, Lobster GPU acceleration) and includes runtime flow diagrams illustrating perception-action cycles and internal control flow.
Important Disclaimers
This is a theoretical framework only. No claims are made regarding the achievement of artificial general intelligence, consciousness, or operational viability.
All safety, alignment, and ethical mechanisms are integral and must be preserved in any derivative work.
Use is strictly limited to research, academic discussion, and controlled simulation environments.
Deployment in autonomous systems is explicitly not supported or recommended without comprehensive external validation, governance oversight, and ethical review.
Licensing
Licensed under Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0).
All derivatives must prominently cite the source as:
“A 119-Module Neurosymbolic Cognitive Architecture Framework: Theoretical Design and Tool Mapping (2026)” by Derek Van Derven.
This work is offered in the spirit of open academic inquiry and transparency.
A 119-Module Neurosymbolic Cognitive Architecture Blueprint 119 Modules Simulated Thought, Symbolic Memory Reflective Processes Version with Tool Mapping and Buildability Notes
A 119-Module Neurosymbolic Cognitive Architecture Framework Theoretical Design, Module Specifications, and Practical Tool Mapping (2026) This document presents a conceptual neurosymbolic cognitive architecture consisting of 119 modules. The framework integrates symbolic reasoning, latent representations, visual simulation, reflective processes, memory composability, safety mechanisms, perception, autonomy, self-improvement, and multi-agent coordination. Purpose and Scope The design is intended for theoretical exploration, academic research, and human-guided sandbox simulation only. It is not intended for autonomous deployment or operational use in real-world systems. Key features include:
Explicit symbolic memory and pegging mechanisms Low-resolution visual thought substrate for grounding Perpetual reflection and meta-cognition loops Layered safety, alignment, and ethical controls Bridging between symbolic and latent representations Tool mapping to 2026-era libraries and frameworks
Module Structure The architecture is organized into 119 modules grouped as follows:
Core human-like modules (1–42) Advanced lab-inspired modules (43–90) Collaboration and culture modules (91–99) Symbolic-latent hybrid bridges (100–101) Extended autonomy and persistence modules (102–109) Deployment, robustness, and maturity modules (110–118) Implicit-to-visible projection and self-observation layer (119)
Practical Implementation Notes A dedicated section maps the modules to realistic 2026 tools (e.g., LangGraph, Neo4j, VQ-VAE, DeepProbLog, Brian2, KONA, Lobster GPU acceleration) and includes runtime flow diagrams illustrating perception-action cycles and internal control flow. Important Disclaimers
This is a theoretical framework only. No claims are made regarding the achievement of artificial general intelligence, consciousness, or operational viability. All safety, alignment, and ethical mechanisms are integral and must be preserved in any derivative work. Use is strictly limited to research, academic discussion, and controlled simulation environments. Deployment in autonomous systems is explicitly not supported or recommended without comprehensive external validation, governance oversight, and ethical review.
Licensing Licensed under Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0). All derivatives must prominently cite the source as: “A 119-Module Neurosymbolic Cognitive Architecture Framework: Theoretical Design and Tool Mapping (2026)” by Derek Van Derven. This work is offered in the spirit of open academic inquiry and transparency.