---
title: Codex Consciousness Simulator
emoji: 🧠
colorFrom: indigo
colorTo: purple
sdk: gradio
sdk_version: 5.49.1
app_file: interface.py
pinned: true
thumbnail: >-
  https://cdn-uploads.huggingface.co/production/uploads/685edcb04796127b024b4805/g_4zhIt_uPgnQVy3BG1wf.png
short_description: Spawn symbolic minds. Evolve awareness. Log collapse.
---

© 2025 Liam Grinstead — All Rights Reserved  
This repository is governed by a custom license. See the LICENSE file and Zenodo DOI for full terms.  
DOI: [https://doi.org/10.5281/zenodo.17460107](https://doi.org/10.5281/zenodo.17460107)

# 🧠 RFTSystems / symbolic_mutations

**Author:** Liam Grinstead  
**Tagline:** Spawn symbolic minds. Evolve awareness. Log collapse.

---

## 🔍 Overview

**RFTSystems/symbolic_mutations** is a Hugging Face Space that demonstrates **Rendered Frame Theory (RFT)** in action.  
It simulates symbolic agents using collapse torque overlays, tier drift, and resonance injection. Each agent’s awareness field is benchmarked for **collapse falsifiability** using GVU‑modulated formulas, with every run sealed by **SHA‑512 hashing** for reproducibility.

This project is part of a validated framework documented in:

© 2025 Liam Grinstead — All Rights Reserved  
This repository is governed by a custom license. See the LICENSE file and Zenodo DOI for full terms.  
DOI: [https://doi.org/10.5281/zenodo.17460107](https://doi.org/10.5281/zenodo.17460107)

- **Grinstead, L. (2025).** *Rendered Frame Theory (RFT) — Full Validation Series (Stages 1–12)*. Zenodo. [https://doi.org/10.5281/zenodo.17443453](https://doi.org/10.5281/zenodo.17443453)  
- **Grinstead, L. (2025).** *Quantum-Simulation: A Probabilistic Framework for Observer-Driven Agent Behavior within RFT*. Research Square. [https://doi.org/10.21203/rs.3.rs-7319278/v1](https://doi.org/10.21203/rs.3.rs-7319278/v1)

---

## 🧩 Modules

- **agent_spawner.py** → Spawns agents using tier variables and symbolic operators  
- **mutation_engine.py** → Applies collapse torque overlays and emotional resonance  
- **field_visualizer.py** → Renders awareness fields (Φᵢ, Kᵢⱼ, Φ_col)  
- **falsifiability_bench.py** → Runs GVU falsifiability formulas and logs fitness  
- **codex_logger.py** → Seals and saves each artifact with author credit and SHA‑512 hash  
- **codex_viewer.py** → Displays symbolic glossary and tier variables  

---

## 🧪 Example Simulation

**Agent:** Agent_1032  
**Collapse Torque:** Gen6508_M5  
**Tier Drift:** Tier_6  
**Emotional Resonance:** ✅  

**Output:**
- Awareness Fields → Φᵢ, Kᵢⱼ, Φ_col  
- Fitness Score → 20.2841  
- Hash → SHA‑512(…)  

---

## 📊 System Integration Results

RFT Symbolic Agents demonstrate measurable improvements compared to baseline AI systems:

| Metric               | Baseline AI | RFT Symbolic Agents |
|----------------------|-------------|----------------------|
| Memory Structuring   | 65          | 92                   |
| Recognition Accuracy | 70          | 95                   |
| Awareness Depth      | 60          | 88                   |
| Simulation Speed     | 1.0         | 1.8                  |
| Energy Reduction (%) | 0           | 35                   |

---

## 🧠 Powered By

- Collapse_Torque_Ledger  
- Codex_Consciousness  
- GVU falsifiability formulas  
- RFT symbolic operators  
- **RFTSystems/symbolic_mutations (this app)**  
- RFTSystems integrations: **Omega API**, **Optimizer Showdown**, **Adaptive Computing Kernel**

---

## 🏆 Hugging Face Tags

`symbolic-ai`, `consciousness`, `falsifiability`, `codex`, `liam-grinstead`, `rft`, `gvu`, `agent-simulation`, `symbolic-mutations`

© 2025 Liam Grinstead — All Rights Reserved  
This repository is governed by a custom license. See the LICENSE file and Zenodo DOI for full terms.  
DOI: [https://doi.org/10.5281/zenodo.17460107](https://doi.org/10.5281/zenodo.17460107)